Managing contingency capacity of pooled resources in multiple availability zones

ABSTRACT

A network-based services provider may reserve and provision primary resource instance capacity for a given service (e.g., enough compute instances, storage instances, or other virtual resource instances to implement the service) in one or more availability zones, and may designate contingency resource instance capacity for the service in another availability zone (without provisioning or reserving the contingency instances for the exclusive use of the service). For example, the service provider may provision resource instance(s) for a database engine head node in one availability zone and designate resource instance capacity for another database engine head node in another availability zone without instantiating the other database engine head node. While the service operates as expected using the primary resource instance capacity, the contingency resource capacity may be leased to other entities on a spot market. Leases for contingency instance capacity may be revoked when needed for the given service (e.g., during failover).

This application is a continuation of U.S. patent application Ser. No.13/894,969, filed May 15, 2013, now U.S. Pat. No. 9,208,032, which ishereby incorporated by reference herein in its entirety.

BACKGROUND

The advent of virtualization technologies for commodity hardware hasprovided benefits with respect to managing large-scale computingresources for many customers with diverse needs, allowing variouscomputing resources to be efficiently and securely shared by multiplecustomers. For example, virtualization technologies may allow a singlephysical computing machine to be shared among multiple users byproviding each user with one or more virtual machines hosted by thesingle physical computing machine, with each such virtual machine beinga software simulation acting as a distinct logical computing system thatprovides users with the illusion that they are the sole operators andadministrators of a given hardware computing resource, while alsoproviding application isolation and security among the various virtualmachines. Furthermore, some virtualization technologies are capable ofproviding virtual resources that span two or more physical resources,such as a single virtual machine with multiple virtual processors thatspans multiple distinct physical computing systems. As another example,virtualization technologies may allow data storage hardware to be sharedamong multiple users by providing each user with a virtualized datastore (e.g., a database) which may be distributed across multiple datastorage devices, with each such virtualized data store acting as adistinct logical data store that provides users with the illusion thatthey are the sole operators and administrators of the data storageresource.

In many environments, operators of provider networks that implementdifferent types of virtualized computing, storage, and/or othernetwork-accessible functionality allow customers to reserve or purchaseaccess to resources in any of several different resource acquisitionmodes. For example, a customer may reserve a virtual compute resourceinstance for a relatively long duration, such as one year or threeyears, or a customer may purchase resources for shorter terms on anad-hoc basis as needed. For some types of resource reservations, atleast a portion of the price paid by the customer may fluctuate overtime in response to changing demand and supply of the resources withinthe provider network. The provider network operator may have to try toensure that a number of potentially competing demands are met, e.g.,that all guaranteed commitments to clients (such as long-termreservations that have already been paid for) are honored, that thedynamically-varying component of resource pricing does not get so highthat customer satisfaction suffers, that the provider's data centerinvestment is justified by a reasonable level of resource utilizationand revenue, and so on. In business environments where clients maychoose from among multiple providers for network-based computingoptions, provider network operators may wish to maintain high levels ofcustomer satisfaction and customer retention, e.g., by making resourceacquisition easy and economical, and by reducing the complexity ofclient resource budget management as much as possible. The serviceprovider must also balance the competing goals of providing highdurability and/or availability (e.g., in the face of node or networkfailures) while avoiding situations in which large numbers of redundantresource instances that are provisioned to provide durability and/oravailability to clients lay idle most, if not all, of the time.

One type of network-based service that is offered to clients is adatabase service. While distribution of various components of a softwarestack can in some cases provide (or support) fault tolerance (e.g.,through replication), higher durability, and less expensive solutions(e.g., through the use of many smaller, less-expensive components ratherthan fewer large, expensive components), databases have historicallybeen among the components of the software stack that are least amenableto distribution. For example, it can be difficult to distributedatabases while still ensuring the so-called ACID properties (e.g.,Atomicity, Consistency, Isolation, and Durability) that they areexpected to provide. In traditional database systems, the data managedby a database system is stored on direct attached disks. If a diskfails, it is replaced and then must be reloaded with the appropriatedata. For example, in many systems, crash recovery includes restoringthe most recent snapshot from a backup system and then replaying anychanges made since the last snapshot from that point forward. However,this approach does not scale well to large databases. In addition, inorder to recover quickly from a crash, such systems often must provisionredundant hardware, software, and/or network resources (at considerableexpense) that are rarely, if ever, used.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating various components of a databasesoftware stack, according to one embodiment.

FIG. 2 is a block diagram illustrating a service system architecturethat may be configured to implement a web services-based databaseservice, according to some embodiments.

FIG. 3 is a block diagram illustrating various components of a databasesystem that includes a database engine and a separate distributeddatabase storage service, according to one embodiment.

FIG. 4 is a block diagram illustrating a distributed database-optimizedstorage system, according to one embodiment.

FIG. 5 is a flow diagram illustrating one embodiment of a method foraccessing data in a database system that includes a database engine anda separate distributed database storage service.

FIG. 6 is a block diagram illustrating the use of a separate distributeddatabase-optimized storage system in a database system, according to oneembodiment.

FIG. 7 is a flow diagram illustrating one embodiment of a method forperforming a write operation in a database system, from the perspectiveof the database engine.

FIG. 8 is a flow diagram illustrating one embodiment of a method forperforming a write operation in a database system, from the perspectiveof a distributed database-optimized storage system.

FIG. 9 is a flow diagram illustrating one embodiment of a method forperforming a read operation in a database system, from the perspectiveof the database engine.

FIG. 10 is a flow diagram illustrating one embodiment of a method forperforming a read operation in a database system, from the perspectiveof a distributed database-optimized storage system.

FIG. 11 is a flow diagram illustrating one embodiment of a method forperforming read and write operations in a distributed database-optimizedstorage system that includes protection groups.

FIG. 12 is a block diagram illustrating one embodiment of a system thatis configured to provide network-based services to clients.

FIG. 13 is a block diagram illustrating an example resource instanceclassification approach, according to one embodiment.

FIG. 14 is a block diagram illustrating one embodiment of a system thatis configured to fulfill resource instance requests using reserved,contingency, and/or interruptible (spot) resource instances.

FIG. 15 is a block diagram illustrating an example application packagethat may be submitted by a client to a resource manager, according toone embodiment.

FIG. 16 is a flow diagram illustrating one embodiment of a method formanaging contingency resource instance capacity by a scalable databaseservice provider.

FIG. 17 is a flow diagram illustrating one embodiment of a method fordesignating contingency resource instances in response to a clientrequest for deployment of a service across availability zones.

FIG. 18 is a flow diagram illustrating one embodiment of a method formanaging contingency resource instance capacity for a database orstorage service.

FIG. 19 is a flow diagram illustrating one embodiment of a method formanaging contingency resource instance capacity by a web-based servicesprovider.

FIG. 20 is a block diagram illustrating a computer system configured toimplement at least a portion of a system that provides web-basedservices using reserved, contingency, and/or interruptible resourceinstance capacity, according to various embodiments.

While embodiments are described herein by way of example for severalembodiments and illustrative drawings, those skilled in the art willrecognize that the embodiments are not limited to the embodiments ordrawings described. It should be understood, that the drawings anddetailed description thereto are not intended to limit embodiments tothe particular form disclosed, but on the contrary, the intention is tocover all modifications, equivalents and alternatives falling within thespirit and scope as defined by the appended claims. The headings usedherein are for organizational purposes only and are not meant to be usedto limit the scope of the description or the claims. As used throughoutthis application, the word “may” is used in a permissive sense (i.e.,meaning having the potential to), rather than the mandatory sense (i.e.,meaning must). Similarly, the words “include,” “including,” and“includes” mean including, but not limited to.

DETAILED DESCRIPTION

The systems described herein may, in some embodiments, providenetwork-based virtual computing services to clients, which may includedatabase services, data storage services, or computation services, amongothers. In order to provide durability and/or availability ofapplications executed using these services and/or client data used orgenerated by them, these systems may provision redundant resourceinstances for the services or may designate redundant resource instancesas contingency resource instances for the services (e.g., in differentavailability zones than those in which the primary resource instancecapacity for the services is provisioned or in the same availabilityzone). In some embodiments, while they are not being used to implementthe service(s) for which they were designated as contingency resourceinstances, at least some of the contingency resource instances may beoffered for lease to others (e.g., other clients, services, applicationsor processes) on a spot market. For example, while contingency resourceinstances may not be reserved or provisioned for the exclusive use of aparticular service until and unless they are needed, they may bereclaimed for the use of the service for which they were designated ascontingency resource instances at any time (e.g., to be activated aspart of a crash recovery process, to allow the service to be furtherscaled, in order to perform maintenance on machines hosting the primaryresource capacity, to improve performance, or for other purposes).

The systems described herein may, in some embodiments, implement a webservice that enables clients (e.g., subscribers) to operate a datastorage system in a cloud computing environment. In some embodiments,the data storage system may be an enterprise-class database system thatis highly scalable and extensible. In some embodiments, queries may bedirected to database storage that is distributed across multiplephysical resources, and the database system may be scaled up or down onan as needed basis. The database system may work effectively withdatabase schemas of various types and/or organizations, in differentembodiments. In some embodiments, clients/subscribers may submit queriesin a number of ways, e.g., interactively via an SQL interface to thedatabase system. In other embodiments, external applications andprograms may submit queries using Open Database Connectivity (ODBC)and/or Java Database Connectivity (JDBC) driver interfaces to thedatabase system.

More specifically, the systems described herein may, in someembodiments, implement a service-oriented database architecture in whichvarious functional components of a single database system areintrinsically distributed. For example, rather than lashing togethermultiple complete and monolithic database instances (each of which mayinclude extraneous functionality, such as an application server, searchfunctionality, or other functionality beyond that required to providethe core functions of a database), these systems may organize the basicoperations of a database (e.g., query processing, transactionmanagement, caching and storage) into tiers that may be individually andindependently scalable. For example, in some embodiments, each databaseinstance in the systems described herein may include a database tier(which may include a single database engine head node and a client-sidestorage system driver), and a separate, distributed storage system(which may include multiple storage nodes that collectively perform someof the operations traditionally performed in the database tier ofexisting systems).

As described in more detail herein, in some embodiments, some of thelowest level operations of a database, (e.g., backup, restore, snapshot,recovery, and/or various space management operations) may be offloadedfrom the database engine to the storage layer and distributed acrossmultiple nodes and storage devices. For example, in some embodiments,rather than the database engine applying changes to database tables (ordata pages thereof) and then sending the modified data pages to thestorage layer, the application of changes to the stored database tables(and data pages thereof) may be the responsibility of the storage layeritself. In such embodiments, redo log records, rather than modified datapages, may be sent to the storage layer, after which redo processing(e.g., the application of the redo log records) may be performedsomewhat lazily and in a distributed manner (e.g., by a backgroundprocess). In some embodiments, crash recovery (e.g., the rebuilding ofdata pages from stored redo log records) may also be performed by thestorage layer and may also be performed by a distributed (and, in somecases, lazy) background process.

In some embodiments, because only redo logs (and not modified datapages) are sent to the storage layer, there may be much less networktraffic between the database tier and the storage layer than in existingdatabase systems. In some embodiments, each redo log may be on the orderof one-tenth the size of the corresponding data page for which itspecifies a change. Note that requests sent from the database tier andthe distributed storage system may be asynchronous and that multiplesuch requests may be in flight at a time.

As previously noted, in typical large database systems, the entire dataset needs to be restored before the database system can be restartedfollowing a failure in the system. In these database systems, followinga crash, the system must determine the last point at which it was knownthat all of the data pages had been flushed to disk (e.g., a checkpoint)and must replay any change logs from that point forward. For example,before the database can be made available to handle incoming queriesfrom client processes, a system process must read in all of the datapages that were changed after the determined checkpoint and apply eachof the applicable change log records that had not already been appliedto those data pages.

In some embodiments, the database systems described herein may be ableto restart the database engine following a failure (e.g., to make thedatabase available to accept and service queries) almost immediatelyafter a database crash, without having to wait for the entire data setto be restored. Instead, queries can be received and serviced whilecrash recovery is performed lazily by one or more background threads.For example, following a crash, multiple background threads may operatein parallel on different storage nodes to reconstruct data pages fromcorresponding redo logs. In the meantime, if an incoming query targets adata page that has not yet been reconstructed, the storage layer may beconfigured to re-create that data page on the fly from the appropriateredo logs.

In some embodiments, the database systems described herein may bedeployed across multiple “availability zones”, each of which may includeits own physically distinct, independent infrastructure on which acollection of computing nodes (e.g., computing nodes on which storagesystem server nodes and/or database engine head nodes are implemented).In some embodiments, each availability zone may reside in a differentlocation or region, while in other embodiments multiple availabilityzones may reside in the same location or region. As described in moredetail herein, in some embodiments, the database systems may provisionprimary resource instance capacity for a given database in oneavailability zone (e.g., enough resource instance capacity to implementa database engine head node and one or more storage system server nodes,along with corresponding storage devices), may provision additionalresource instance capacity for the given database in anotheravailability zone (e.g., enough resource instance capacity to implementone or more redundant storage system server nodes, along withcorresponding storage devices storing replicas of the data stored in theprimary availability zone), and may designate still other resourceinstances (e.g., enough resource instance capacity to implement anadditional or replacement database engine head node, if needed) ascontingency resource capacity for the database in the other availabilityzone.

In general, after being given a piece of data, a primary requirement ofa database is that it can eventually give that piece of data back. To dothis, the database may include several different components (or tiers),each of which performs a different function. For example, a traditionaldatabase may be thought of as having three tiers: a first tier forperforming query parsing, optimization and execution; a second tier forproviding transactionality, recovery, and durability; and a third tierthat provides storage, either on locally attached disks or onnetwork-attached storage. As noted above, previous attempts to scale atraditional database have typically involved replicating all three tiersof the database and distributing those replicated database instancesacross multiple machines.

In some embodiments, the systems described herein may partitionfunctionality of a database system differently than in a traditionaldatabase, and may distribute only a subset of the functional components(rather than a complete database instance) across multiple machines inorder to implement scaling. For example, in some embodiments, aclient-facing tier may be configured to receive a request specifyingwhat data is to be stored or retrieved, but not how to store or retrievethe data. This tier may perform request parsing and/or optimization(e.g., SQL parsing and optimization), while another tier may beresponsible for query execution. In some embodiments, a third tier maybe responsible for providing transactionality and consistency ofresults. For example, this tier may be configured to enforce some of theso-called ACID properties, in particular, the Atomicity of transactionsthat target the database, maintaining Consistency within the database,and ensuring Isolation between the transactions that target thedatabase. In some embodiments, a fourth tier may then be responsible forproviding Durability of the stored data in the presence of various sortsof faults. For example, this tier may be responsible for change logging,recovery from a database crash, managing access to the underlyingstorage volumes and/or space management in the underlying storagevolumes.

FIG. 1 is a block diagram illustrating various components of a databasesoftware stack, according to one embodiment. As illustrated in thisexample, a database instance may include multiple functional components(or layers), each of which provides a portion of the functionality ofthe database instance. In this example, database instance 100 includes aquery parsing and query optimization layer (shown as 110), a queryexecution layer (shown as 120), a transactionality and consistencymanagement layer (shown as 130), and a durability and space managementlayer (shown as 140). As noted above, in some existing database systems,scaling a database instance may involve duplicating the entire databaseinstance one or more times (including all of the layers illustrated inFIG. 1), and then adding glue logic to stitch them together. In someembodiments, the systems described herein may instead offload thefunctionality of durability and space management layer 140 from thedatabase tier to a separate storage layer, and may distribute thatfunctionality across multiple storage nodes in the storage layer.

In some embodiments, the database systems described herein may retainmuch of the structure of the upper half of the database instanceillustrated in FIG. 1, but may redistribute responsibility for at leastportions of the backup, restore, snapshot, recovery, and/or variousspace management operations to the storage tier. Redistributingfunctionality in this manner and tightly coupling log processing betweenthe database tier and the storage tier may improve performance, increaseavailability and reduce costs, when compared to previous approaches toproviding a scalable database. For example, network and input/outputbandwidth requirements may be reduced, since only redo log records(which are much smaller in size than the actual data pages) may beshipped across nodes or persisted within the latency path of writeoperations. In addition, the generation of data pages can be doneindependently in the background on each storage node (as foregroundprocessing allows), without blocking incoming write operations. In someembodiments, the use of log-structured, non-overwrite storage may allowbackup, restore, snapshots, point-in-time recovery, and volume growthoperations to be performed more efficiently, e.g., by using onlymetadata manipulation rather than movement or copying of a data page. Insome embodiments, the storage layer may also assume the responsibilityfor the replication of data stored on behalf of clients (and/or metadataassociated with that data, such as redo log records) across multiplestorage nodes. For example, data (and/or metadata) may be replicatedlocally (e.g., within a single availability zone) and/or acrossavailability zones in a single region or in different regions. In someembodiments, the decision about whether to replicate data (and/ormetadata) locally or across multiple availability zones may be dependenton a system-wide (default) policy, an application-specific orclient-specific policy, or a client preference (e.g., a request by acustomer or service subscriber, or a parameter value specified by acustomer/subscriber as part of a request to receive database services orto create a particular database instance.

In various embodiments, the database systems described herein maysupport a standard or custom application programming interface (API) fora variety of database operations. For example, the API may supportoperations for creating a database, creating a table, altering a table,creating a user, dropping a user, inserting one or more rows in a table,copying values, selecting data from within a table (e.g., querying atable), cancelling or aborting a query, and/or other operations.

In some embodiments, the database tier of a database instance mayinclude a database engine head node server that receives read and/orwrite requests from various client programs (e.g., applications) and/orsubscribers (users), then parses them and develops an execution plan tocarry out the associated database operation(s). For example, thedatabase engine head node may develop the series of steps necessary toobtain results for complex queries and joins. In some embodiments, thedatabase engine head node may manage communications between the databasetier of the database system and clients/subscribers, as well ascommunications between the database tier and a separate distributeddatabase-optimized storage system.

In some embodiments, the database engine head node may be responsiblefor receiving SQL requests from end clients through a JDBC or ODBCinterface and for performing SQL processing and transaction management(which may include locking) locally. However, rather than generatingdata pages locally, the database engine head node (or various componentsthereof) may generate redo log records and may ship them to theappropriate nodes of a separate distributed storage system. In someembodiments, a client-side driver for the distributed storage system maybe hosted on the database engine head node and may be responsible forrouting redo log records to the storage system node (or nodes) thatstore the segments (or data pages thereof) to which those redo logrecords are directed. For example, in some embodiments, each segment maybe mirrored (or otherwise made durable) on multiple storage system nodesthat form a protection group. In such embodiments, the client-sidedriver may keep track of the nodes on which each segment is stored andmay route redo logs to all of the nodes on which a segment is stored(e.g., asynchronously and in parallel, at substantially the same time),when a client request is received. As soon as the client-side driverreceives an acknowledgement back from a write quorum of the storagenodes in the protection group (which may indicate that the redo logrecord has been written to the storage node), it may send anacknowledgement of the requested change to the database tier (e.g., tothe database engine head node). For example, in embodiments in whichdata is made durable through the use of protection groups, the databaseengine head node may not be able to commit a transaction until andunless the client-side driver receives a reply from enough storage nodeinstances to constitute a write quorum. Similarly, for a read requestdirected to a particular segment, the client-side driver may route theread request to all of the nodes on which the segment is stored (e.g.,asynchronously and in parallel, at substantially the same time). As soonas the client-side driver receives the requested data from a read quorumof the storage nodes in the protection group, it may return therequested data to the database tier (e.g., to the database engine headnode).

In some embodiments, the database tier (or more specifically, thedatabase engine head node) may include a cache in which recentlyaccessed data pages are held temporarily. In such embodiments, if awrite request is received that targets a data page held in such a cache,in addition to shipping a corresponding redo log record to the storagelayer, the database engine may apply the change to the copy of the datapage held in its cache. However, unlike in other database systems, adata page held in this cache may not ever be flushed to the storagelayer, and it may be discarded at any time (e.g., at any time after theredo log record for a write request that was most recently applied tothe cached copy has been sent to the storage layer and acknowledged).The cache may implement any of various locking mechanisms to controlaccess to the cache by at most one writer (or multiple readers) at atime, in different embodiments. Note, however, that in embodiments thatinclude such a cache, the cache may not be distributed across multiplenodes, but may exist only on the database engine head node for a givendatabase instance. Therefore, there may be no cache coherency orconsistency issues to manage.

In some embodiments, the database tier may support the use ofsynchronous or asynchronous read replicas in the system, e.g., read-onlycopies of data on different nodes of the database tier to which readrequests can be routed. In such embodiments, if the database engine headnode for a given database table receives a read request directed to aparticular data page, it may route the request to any one (or aparticular one) of these read-only copies. In some embodiments, theclient-side driver in the database engine head node may be configured tonotify these other nodes about updates and/or invalidations to cacheddata pages (e.g., in order to prompt them to invalidate their caches,after which they may request updated copies of updated data pages fromthe storage layer).

In some embodiments, the client-side driver running on the databaseengine head node may expose a private interface to the storage tier. Insome embodiments, it may also expose a traditional iSCSI interface toone or more other components (e.g., other database engines or virtualcomputing services components). In some embodiments, storage for adatabase instance in the storage tier may be modeled as a single volumethat can grow in size without limits, and that can have an unlimitednumber of IOPS associated with it. When a volume is created, it may becreated with a specific size, with a specific availability/durabilitycharacteristic (e.g., specifying how it is replicated), and/or with anIOPS rate associated with it (e.g., both peak and sustained). Forexample, in some embodiments, a variety of different durability modelsmay be supported, and users/subscribers may be able to specify, fortheir database tables, a number of replication copies, zones, or regionsand/or whether replication is synchronous or asynchronous based upontheir durability, performance and cost objectives.

In some embodiments, the client side driver may maintain metadata aboutthe volume and may directly send asynchronous requests to each of thestorage nodes necessary to fulfill read requests and write requestswithout requiring additional hops between storage nodes. For example, insome embodiments, in response to a request to make a change to adatabase table, the client-side driver may be configured to determinethe one or more nodes that are implementing the storage for the targeteddata page, and to route the redo log record(s) specifying that change tothose storage nodes. The storage nodes may then be responsible forapplying the change specified in the redo log record to the targeteddata page at some point in the future. As writes are acknowledged backto the client-side driver, the client-side driver may advance the pointat which the volume is durable and may acknowledge commits back to thedatabase tier. As previously noted, in some embodiments, the client-sidedriver may not ever send data pages to the storage node servers. Thismay not only reduce network traffic, but may also remove the need forthe checkpoint or background writer threads that constrainforeground-processing throughput in previous database systems. Note thatin embodiments in which data is replicated on multiple storage systemnodes in multiple availability zones, the client side driver may beconfigured to send asynchronous requests (including, for example, redolog records) to storage system nodes in availability zones other thanthe one in which the database engine head node is located.

In some embodiments, many read requests may be served by the databaseengine head node cache. However, write requests may require durability,since large-scale failure events may be too common to allow onlyin-memory replication. Therefore, the systems described herein may beconfigured to minimize the cost of the redo log record write operationsthat are in the foreground latency path by implementing data storage inthe storage tier as two regions: a small append-only log-structuredregion into which redo log records are written when they are receivedfrom the database tier, and a larger region in which log records arecoalesced together to create new versions of data pages in thebackground. In some embodiments, an in-memory structure may bemaintained for each data page that points to the last redo log recordfor that page, backward chaining log records until an instantiated datablock is referenced. This approach may provide good performance formixed read-write workloads, including in applications in which reads arelargely cached.

In some embodiments, because accesses to the log-structured data storagefor the redo log records may consist of a series of sequentialinput/output operations (rather than random input/output operations),the changes being made may be tightly packed together. It should also benoted that, in contrast to existing systems in which each change to adata page results in two input/output operations to persistent datastorage (one for the redo log and one for the modified data pageitself), in some embodiments, the systems described herein may avoidthis “write amplification” by coalescing data pages at the storage nodesof the distributed storage system based on receipt of the redo logrecords.

As previously noted, in some embodiments, the storage tier of thedatabase system may be responsible for taking database snapshots.However, because the storage tier implements log-structured storage,taking a snapshot of a data page (e.g., a data block) may includerecording a timestamp associated with the redo log record that was mostrecently applied to the data page/block (or a timestamp associated withthe most recent operation to coalesce multiple redo log records tocreate a new version of the data page/block), and preventing garbagecollection of the previous version of the page/block and any subsequentlog entries up to the recorded point in time. For example, taking adatabase snapshot may not require reading, copying, or writing the datablock, as would be required when employing an off-volume backupstrategy. In some embodiments, the space requirements for snapshots maybe minimal, since only modified data would require additional space,although user/subscribers may be able to choose how much additionalspace they want to keep for on-volume snapshots in addition to theactive data set. In different embodiments, snapshots may be discrete(e.g., each snapshot may provide access to all of the data in a datapage as of a specific point in time) or continuous (e.g., each snapshotmay provide access to all versions of the data that existing in a datapage between two points in time). In some embodiments, reverting to aprior snapshot may include recording a log record to indicate that allredo log records and data pages since that snapshot are invalid andgarbage collectable, and discarding all database cache entries after thesnapshot point. In such embodiments, no roll-forward may be requiredsince the storage system will, on a block-by-block basis, apply redo logrecords to data blocks as requested and in the background across allnodes, just as it does in normal forward read/write processing. Crashrecovery may thereby be made parallel and distributed across nodes.

One embodiment of a service system architecture that may be configuredto implement a web services-based database service is illustrated inFIG. 2. In the illustrated embodiment, a number of clients (shown asdatabase clients 250 a-250 n) may be configured to interact with a webservices platform 200 via a network 260. Web services platform 200 maybe configured to interface with one or more instances of a databaseservice 210, a distributed database-optimized storage service 220 and/orone or more other virtual computing services 230. It is noted that whereone or more instances of a given component may exist, reference to thatcomponent herein may be made in either the singular or the plural.However, usage of either form is not intended to preclude the other.

In various embodiments, the components illustrated in FIG. 2 may beimplemented directly within computer hardware, as instructions directlyor indirectly executable by computer hardware (e.g., a microprocessor orcomputer system), or using a combination of these techniques. Forexample, the components of FIG. 2 may be implemented by a system thatincludes a number of computing nodes (or simply, nodes), each of whichmay be similar to the computer system embodiment illustrated in FIG. 20and described below. In various embodiments, the functionality of agiven service system component (e.g., a component of the databaseservice or a component of the storage service) may be implemented by aparticular node or may be distributed across several nodes. In someembodiments, a given node may implement the functionality of more thanone service system component (e.g., more than one database servicesystem component).

Generally speaking, clients 250 may encompass any type of client that isconfigured to submit web services requests to web services platform 200via network 260, including requests for database services. For example,a given client 250 may include a suitable version of a web browser, ormay include a plug-in module or other type of code module configured toexecute as an extension to or within an execution environment providedby a web browser. Alternatively, a client 250 (e.g., a database serviceclient) may encompass an application such as a database application (oruser interface thereof), a media application, an office application orany other application that may make use of persistent storage resourcesto store and/or access one or more database tables. In some embodiments,such an application may include sufficient protocol support (e.g., for asuitable version of Hypertext Transfer Protocol (HTTP)) for generatingand processing web services requests without necessarily implementingfull browser support for all types of web-based data. That is, client250 may be an application configured to interact directly with webservices platform 200. In some embodiments, client 250 may be configuredto generate web services requests according to a Representational StateTransfer (REST)-style web services architecture, a document- ormessage-based web services architecture, or another suitable webservices architecture.

In some embodiments, a client 250 (e.g., a database service client) maybe configured to provide access to web services-based storage ofdatabase tables to other applications in a manner that is transparent tothose applications. For example, client 250 may be configured tointegrate with an operating system or file system to provide storage inaccordance with a suitable variant of the storage models describedherein. However, the operating system or file system may present adifferent storage interface to applications, such as a conventional filesystem hierarchy of files, directories and/or folders. In such anembodiment, applications may not need to be modified to make use of thestorage system service model of FIG. 1. Instead, the details ofinterfacing to Web services platform 200 may be coordinated by client250 and the operating system or file system on behalf of applicationsexecuting within the operating system environment.

Clients 250 may convey web services requests to and receive responsesfrom web services platform 200 via network 260. In various embodiments,network 260 may encompass any suitable combination of networkinghardware and protocols necessary to establish web-based communicationsbetween clients 250 and platform 200. For example, network 260 maygenerally encompass the various telecommunications networks and serviceproviders that collectively implement the Internet. Network 260 may alsoinclude private networks such as local area networks (LANs) or wide areanetworks (WANs) as well as public or private wireless networks. Forexample, both a given client 250 and web services platform 200 may berespectively provisioned within enterprises having their own internalnetworks. In such an embodiment, network 260 may include the hardware(e.g., modems, routers, switches, load balancers, proxy servers, etc.)and software (e.g., protocol stacks, accounting software,firewall/security software, etc.) necessary to establish a networkinglink between given client 250 and the Internet as well as between theInternet and web services platform 200. It is noted that in someembodiments, clients 250 may communicate with web services platform 200using a private network rather than the public Internet. For example,clients 250 may be provisioned within the same enterprise as a databaseservice system (e.g., a system that implements database service 210and/or distributed database-optimized storage service 220). In such acase, clients 250 may communicate with platform 200 entirely through aprivate network 260 (e.g., a LAN or WAN that may use Internet-basedcommunication protocols but which is not publicly accessible).

Generally speaking, web services platform 200 may be configured toimplement one or more service endpoints configured to receive andprocess web services requests, such as requests to access data pages (orrecords thereof). For example, web services platform 200 may includehardware and/or software configured to implement a particular endpoint,such that an HTTP-based web services request directed to that endpointis properly received and processed. In one embodiment, web servicesplatform 200 may be implemented as a server system configured to receiveweb services requests from clients 250 and to forward them to componentsof a system that implements database service 210, distributeddatabase-optimized storage service 220 and/or another virtual computingservice 230 for processing. In other embodiments, web services platform200 may be configured as a number of distinct systems (e.g., in acluster topology) implementing load balancing and other requestmanagement features configured to dynamically manage large-scale webservices request processing loads. In various embodiments, web servicesplatform 200 may be configured to support REST-style or document-based(e.g., SOAP-based) types of web services requests.

In addition to functioning as an addressable endpoint for clients' webservices requests, in some embodiments, web services platform 200 mayimplement various client management features. For example, platform 200may coordinate the metering and accounting of client usage of webservices, including storage resources, such as by tracking theidentities of requesting clients 250, the number and/or frequency ofclient requests, the size of data tables (or records thereof) stored orretrieved on behalf of clients 250, overall storage bandwidth used byclients 250, class of storage requested by clients 250, or any othermeasurable client usage parameter. Platform 200 may also implementfinancial accounting and billing systems, or may maintain a database ofusage data that may be queried and processed by external systems forreporting and billing of client usage activity. In certain embodiments,platform 200 may be configured to collect, monitor and/or aggregate avariety of storage service system operational metrics, such as metricsreflecting the rates and types of requests received from clients 250,bandwidth utilized by such requests, system processing latency for suchrequests, system component utilization (e.g., network bandwidth and/orstorage utilization within the storage service system), rates and typesof errors resulting from requests, characteristics of stored andrequested data pages or records thereof (e.g., size, data type, etc.),or any other suitable metrics. In some embodiments such metrics may beused by system administrators to tune and maintain system components,while in other embodiments such metrics (or relevant portions of suchmetrics) may be exposed to clients 250 to enable such clients to monitortheir usage of database service 210, distributed database-optimizedstorage service 220 and/or another virtual computing service 230 (or theunderlying systems that implement those services). For example, in someembodiments, the system illustrated in FIG. 2 may provide other types ofdata storage services, temporary caching services, computation services,or any of a variety of stateful or stateless computing services, some ofwhich may be suitable for receiving services through a resource instancespot market.

In some embodiments, platform 200 may also implement user authenticationand access control procedures. For example, for a given web servicesrequest to access a particular database table, platform 200 may beconfigured to ascertain whether the client 250 associated with therequest is authorized to access the particular database table. Platform200 may determine such authorization by, for example, evaluating anidentity, password or other credential against credentials associatedwith the particular database table, or evaluating the requested accessto the particular database table against an access control list for theparticular database table. For example, if a client 250 does not havesufficient credentials to access the particular database table, platform200 may reject the corresponding web services request, for example byreturning a response to the requesting client 250 indicating an errorcondition. Various access control policies may be stored as records orlists of access control information by database service 210, distributeddatabase-optimized storage service 220 and/or other virtual computingservices 230.

It is noted that while web services platform 200 may represent theprimary interface through which clients 250 may access the features of adatabase system that implements database service 210, it need notrepresent the sole interface to such features. For example, an alternateAPI that may be distinct from a web services interface may be used toallow clients internal to the enterprise providing the database systemto bypass web services platform 200. Note that in many of the examplesdescribed herein, distributed database-optimized storage service 220 maybe internal to a computing system or an enterprise system that providesdatabase services to clients 250, and may not be exposed to externalclients (e.g., users or client applications). In such embodiments, theinternal “client” (e.g., database service 210) may access distributeddatabase-optimized storage service 220 over a local or private network,shown as the solid line between distributed database-optimized storageservice 220 and database service 210 (e.g., through an API directlybetween the systems that implement these services). In such embodiments,the use of distributed database-optimized storage service 220 in storingdatabase tables on behalf of clients 250 may be transparent to thoseclients. In other embodiments, distributed database-optimized storageservice 220 may be exposed to clients 250 through web services platform200 to provide storage of database tables or other information forapplications other than those that rely on database service 210 fordatabase management. This is illustrated in FIG. 2 by the dashed linebetween web services platform 200 and distributed database-optimizedstorage service 220. In such embodiments, clients of the distributeddatabase-optimized storage service 220 may access distributeddatabase-optimized storage service 220 via network 260 (e.g., over theInternet). In some embodiments, a virtual computing service 230 may beconfigured to receive storage services from distributeddatabase-optimized storage service 220 (e.g., through an API directlybetween the virtual computing service 230 and distributeddatabase-optimized storage service 220) to store objects used inperforming computing services 230 on behalf of a client 250. This isillustrated in FIG. 2 by the dashed line between virtual computingservice 230 and distributed database-optimized storage service 220. Inother embodiments, virtual computing service 230 may be a distinctvirtual computing service offering that is distinct from (and unrelatedto distributed database-optimized storage service 220 and/or databaseservice 210) In some cases, the accounting and/or credentialing servicesof platform 200 may be unnecessary for internal clients such asadministrative clients or between service components within the sameenterprise.

Note that in various embodiments, different storage policies may beimplemented by database service 210 and/or distributeddatabase-optimized storage service 220. Examples of such storagepolicies may include a durability policy (e.g., a policy indicating thenumber of instances of a database table (or data page thereof) that willbe stored and the number of different nodes on which they will bestored) and/or a load balancing policy (which may distribute databasetables, or data pages thereof, across different nodes, volumes and/ordisks in an attempt to equalize request traffic). In addition, differentstorage policies may be applied to different types of stored items byvarious one of the services. For example, in some embodiments,distributed database-optimized storage service 220 may implement ahigher durability for redo log records than for data pages.

FIG. 3 is a block diagram illustrating various components of a databasesystem that includes a database engine and a separate distributeddatabase storage service, according to one embodiment. In this example,database system 300 includes a respective database engine head node 320for each of several database tables and a distributed database-optimizedstorage service 310 (which may or may not be visible to the clients ofthe database system, shown as database clients 350 a-350 n). Asillustrated in this example, one or more of database clients 350 a-350 nmay access a database head node 320 (e.g., head node 320 a, head node320 b, or head node 320 c, each of which is a component of a respectivedatabase instance) via network 360 (e.g., these components may benetwork-addressable and accessible to the database clients 350 a-350 n).However, distributed database-optimized storage service 310, which maybe employed by the database system to store data pages of one or moredatabase tables (and redo log records and/or other metadata associatedtherewith) on behalf of database clients 350 a-350 n, and to performother functions of the database system as described herein, may or maynot be network-addressable and accessible to the storage clients 350a-350 n, in different embodiments. For example, in some embodiments,distributed database-optimized storage service 310 may perform variousstorage, access, change logging, recovery, and/or space managementoperations in a manner that is invisible to storage clients 350 a-350 n.

As previously noted, each database instance may include a singledatabase engine head node 320 that receives requests from various clientprograms (e.g., applications) and/or subscribers (users), then parsesthem, optimizes them, and develops an execution plan to carry out theassociated database operation(s). In the example illustrated in FIG. 3,a query parsing, optimization, and execution component 305 of databaseengine head node 320 a may perform these functions for queries that arereceived from database client 350 a and that target the databaseinstance of which database engine head node 320 a is a component. Insome embodiments, query parsing, optimization, and execution component305 may return query responses to database client 350 a, which mayinclude write acknowledgements, requested data pages (or portionsthereof), error messages, and or other responses, as appropriate. Asillustrated in this example, database engine head node 320 a may alsoinclude a client-side storage service driver 325, which may route readrequests and/or redo log records to various storage nodes withindistributed database-optimized storage service 310, receive writeacknowledgements from distributed database-optimized storage service310, receive requested data pages from distributed database-optimizedstorage service 310, and/or return data pages, error messages, or otherresponses to query parsing, optimization, and execution component 305(which may, in turn, return them to database client 350 a).

In this example, database engine head node 320 a includes a data pagecache 335, in which data pages that were recently accessed may betemporarily held. As illustrated in FIG. 3, database engine head node320 a may also include a transaction and consistency managementcomponent 330, which may be responsible for providing transactionalityand consistency in the database instance of which database engine headnode 320 a is a component. For example, this component may beresponsible for ensuring the Atomicity, Consistency, and Isolationproperties of the database instance and the transactions that aredirected that the database instance. As illustrated in FIG. 3, databaseengine head node 320 a may also include a transaction log 340 and anundo log 345, which may be employed by transaction and consistencymanagement component 330 to track the status of various transactions androll back any locally cached results of transactions that do not commit.

Note that each of the other database engine head nodes 320 illustratedin FIG. 3 (e.g., 320 b and 320 c) may include similar components and mayperform similar functions for queries received by one or more ofdatabase clients 350 a-350 n and directed to the respective databaseinstances of which it is a component.

In some embodiments, the distributed database-optimized storage systemsdescribed herein may organize data in various logical volumes, segments,and pages for storage on one or more storage nodes. For example, in someembodiments, each database table is represented by a logical volume, andeach logical volume is segmented over a collection of storage nodes.Each segment, which lives on a particular one of the storage nodes,contains a set of contiguous block addresses. In some embodiments, eachdata page is stored in a segment, such that each segment stores acollection of one or more data pages and a change log (also referred toas a redo log) for each data page that it stores. As described in detailherein, the storage nodes may be configured to receive redo log records(which may also be referred to herein as ULRs) and to coalesce them tocreate new versions of the corresponding data pages and/or additional orreplacement log records (e.g., lazily and/or in response to a requestfor a data page or a database crash). In some embodiments, data pagesand/or change logs may be mirrored across multiple storage nodes,according to a variable configuration (which may be specified by theclient on whose behalf the database table is being maintained in thedatabase system). For example, in different embodiments, one, two, orthree copies of the data or change logs may be stored in each of one,two, or three different availability zones or regions, according to adefault configuration, an application-specific durability preference, ora client-specified durability preference.

As described in more detail below, in some embodiments, resourceinstances that are used to implement the database systems and/ordistributed database-optimized storage systems described herein mayinclude both reserved resource instances (e.g., resource instances inone or more availability zones that are reserved for the exclusive useof the database system or distributed database-optimized storagesystem), and contingency resource instances in one or more of the sameavailability zones or in an availability zone other than theavailability zone(s) in which the database engine head node and/orstorage system server nodes are implemented (e.g., resource instancesthat are designated for the use of the database system or distributeddatabase-optimized storage system in the event of a condition thatwarrants the activation of an additional or replacement database enginehead node). In some embodiments, these contingency resource instancesmay be leased out (e.g., under a spot market pricing model) when theyare not needed by the database system or distributed database-optimizedstorage system, but those leases may be revoked if and when they areneeded by the database system or distributed database-optimized storagesystem (e.g., to replace reserved resource instances in the case of afailover condition or while performing maintenance operations on one ormore nodes on which the reserved resource instances are implemented, toreplace or supplement reserved resource instances to improve performanceor to support additional scaling, or in response to one or more othertrigger conditions being met).

As used herein, the following terms may be used to describe theorganization of data by a distributed database-optimized storage system,according to various embodiments.

Volume: A volume is a logical concept representing a highly durable unitof storage that a user/client/application of the storage systemunderstands. More specifically, a volume is a distributed store thatappears to the user/client/application as a single consistent orderedlog of write operations to various user pages of a database table. Eachwrite operation may be encoded in a User Log Record (ULR), whichrepresents a logical, ordered mutation to the contents of a single userpage within the volume. As noted above, a ULR may also be referred toherein as a redo log record. Each ULR may include a unique LSN, orLogical Sequence Number. Each ULR may be persisted to one or moresynchronous segments in the distributed store that form a ProtectionGroup (PG), to provide high durability and availability for the ULR. Avolume may provide an LSN-type read/write interface for a variable-sizecontiguous range of bytes.

In some embodiments, a volume may consist of multiple extents, each madedurable through a protection group. In such embodiments, a volume mayrepresent a unit of storage composed of a mutable contiguous sequence ofVolume Extents. Reads and writes that are directed to a volume may bemapped into corresponding reads and writes to the constituent volumeextents. In some embodiments, the size of a volume may be changed byadding or removing volume extents from the end of the volume.

Segment: A segment is a limited-durability unit of storage assigned to asingle storage node. More specifically, a segment provides limitedbest-effort durability (e.g., a persistent, but non-redundant singlepoint of failure that is a storage node) for a specific fixed-size byterange of data. This data may in some cases be a mirror ofuser-addressable data, or it may be other data, such as volume metadataor erasure coded bits, in various embodiments. A given segment may liveon exactly one storage node. Within a storage node, multiple segmentsmay live on each SSD, and each segment may be restricted to one SSD(e.g., a segment may not span across multiple SSDs). In someembodiments, a segment may not be required to occupy a contiguous regionon an SSD; rather there may be an allocation map in each SSD describingthe areas that are owned by each of the segments. As noted above, aprotection group may consist of multiple segments spread across multiplestorage nodes. In some embodiments, a segment may provide an LSN-typeread/write interface for a fixed-size contiguous range of bytes (wherethe size is defined at creation). In some embodiments, each segment maybe identified by a Segment UUID (e.g., a universally unique identifierof the segment).

Storage page: A storage page is a block of memory, generally of fixedsize. In some embodiments, each page is a block of memory (e.g., ofvirtual memory, disk, or other physical memory) of a size defined by theoperating system, and may also be referred to herein by the term “datablock”. More specifically, a storage page may be a set of contiguoussectors. It may serve as the unit of allocation in SSDs, as well as theunit in log pages for which there is a header and metadata. In someembodiments, and in the context of the database systems describedherein, the term “page” or “storage page” may refer to a similar blockof a size defined by the database configuration, which may typically amultiple of 2, such as 4096, 8192, 16384, or 32768 bytes.

Log page: A log page is a type of storage page that is used to store logrecords (e.g., redo log records or undo log records). In someembodiments, log pages may be identical in size to storage pages. Eachlog page may include a header containing metadata about that log page,e.g., metadata identifying the segment to which it belongs. Note that alog page is a unit of organization and may not necessarily be the unitof data included in write operations. For example, in some embodiments,during normal forward processing, write operations may write to the tailof the log one sector at a time.

Log Records: Log records (e.g., the individual elements of a log page)may be of several different classes. For example, User Log Records(ULRs), which are created and understood by users/clients/applicationsof the storage system, may be used to indicate changes to user data in avolume. Control Log Records (CLRs), which are generated by the storagesystem, may contain control information used to keep track of metadatasuch as the current unconditional volume durable LSN (VDL). Null LogRecords (NLRs) may in some embodiments be used as padding to fill inunused space in a log sector or log page. In some embodiments, there maybe various types of log records within each of these classes, and thetype of a log record may correspond to a function that needs to beinvoked to interpret the log record. For example, one type may representall the data of a user page in compressed format using a specificcompression format; a second type may represent new values for a byterange within a user page; a third type may represent an incrementoperation to a sequence of bytes interpreted as an integer; and a fourthtype may represent copying one byte range to another location within thepage. In some embodiments, log record types may be identified by GUIDs(rather than by integers or enums), which may simplify versioning anddevelopment, especially for ULRs.

Payload: The payload of a log record is the data or parameter valuesthat are specific to the log record or to log records of a particulartype. For example, in some embodiments, there may be a set of parametersor attributes that most (or all) log records include, and that thestorage system itself understands. These attributes may be part of acommon log record header/structure, which may be relatively smallcompared to the sector size. In addition, most log records may includeadditional parameters or data specific to that log record type, and thisadditional information may be considered the payload of that log record.In some embodiments, if the payload for a particular ULR is larger thanthe user page size, it may be replaced by an absolute ULR (an AULR)whose payload includes all the data for the user page. This may enablethe storage system to enforce an upper limit on the size of the payloadfor ULRs that is equal to the size of user pages.

Note that when storing log records in the segment log, the payload maybe stored along with the log header, in some embodiments. In otherembodiments, the payload may be stored in a separate location, andpointers to the location at which that payload is stored may be storedwith the log header. In still other embodiments, a portion of thepayload may be stored in the header, and the remainder of the payloadmay be stored in a separate location. If the entire payload is storedwith the log header, this may be referred to as in-band storage;otherwise the storage may be referred to as being out-of-band. In someembodiments, the payloads of most large AULRs may be stored out-of-bandin the cold zone of log (which is described below).

User pages: User pages are the byte ranges (of a fixed size) andalignments thereof for a particular volume that are visible tousers/clients of the storage system. User pages are a logical concept,and the bytes in particular user pages may or not be stored in anystorage page as-is. The size of the user pages for a particular volumemay be independent of the storage page size for that volume. In someembodiments, the user page size may be configurable per volume, anddifferent segments on a storage node may have different user page sizes.In some embodiments, user page sizes may be constrained to be a multipleof the sector size (e.g., 4 KB), and may have an upper limit (e.g., 64KB). The storage page size, on the other hand, may be fixed for anentire storage node and may not change unless there is a change to theunderlying hardware.

Data page: A data page is a type of storage page that is used to storeuser page data in compressed form. In some embodiments every piece ofdata stored in a data page is associated with a log record, and each logrecord may include a pointer to a sector within a data page (alsoreferred to as a data sector). In some embodiments, data pages may notinclude any embedded metadata other than that provided by each sector.There may be no relationship between the sectors in a data page.Instead, the organization into pages may exist only as an expression ofthe granularity of the allocation of data to a segment.

Storage node: A storage node is a single virtual machine that on whichstorage node server code is deployed. Each storage node may containmultiple locally attached SSDs, and may provide a network API for accessto one or more segments. In some embodiments, various nodes may be on anactive list or on a degraded list (e.g., if they are slow to respond orare otherwise impaired, but are not completely unusable). In someembodiments, the client-side driver may assist in (or be responsiblefor) classifying nodes as active or degraded, for determining if andwhen they should be replaced, and/or for determining when and how toredistribute data among various nodes, based on observed performance.

SSD: As referred to herein, the term “SSD” may refer to a local blockstorage volume as seen by the storage node, regardless of the type ofstorage employed by that storage volume, e.g., disk, a solid-statedrive, a battery-backed RAM, an NVMRAM device (e.g., one or moreNVDIMMs), or another type of persistent storage device. An SSD is notnecessarily mapped directly to hardware. For example, a singlesolid-state storage device might be broken up into multiple localvolumes where each volume is split into and striped across multiplesegments, and/or a single drive may be broken up into multiple volumessimply for ease of management, in different embodiments. In someembodiments, each SSD may store an allocation map at a single fixedlocation. This map may indicate which storage pages that are owned byparticular segments, and which of these pages are log pages (as opposedto data pages). In some embodiments, storage pages may be pre-allocatedto each segment so that forward processing may not need to wait forallocation. Any changes to the allocation map may need to be madedurable before newly allocated storage pages are used by the segments.

One embodiment of a distributed database-optimized storage system isillustrated by the block diagram in FIG. 4. In this example, a databasesystem 400 includes a distributed database-optimized storage system 410,which communicates with a database engine head node 420 overinterconnect 460. As in the example illustrated in FIG. 3, databaseengine head node 420 may include a client-side storage service driver425. In this example, distributed database-optimized storage system 410includes multiple storage system server nodes (including those shown as430, 440, and 450), each of which includes storage for data pages andredo logs for the segment(s) it stores, and hardware and/or softwareconfigured to perform various segment management functions. For example,each storage system server node may include hardware and/or softwareconfigured to perform at least a portion of any or all of the followingoperations: replication (locally, e.g., within the storage node),coalescing of redo logs to generate data pages, crash recovery, and/orspace management (e.g., for a segment). Each storage system server nodemay also have multiple attached storage devices (e.g., SSDs) on whichdata blocks may be stored on behalf of clients (e.g., users, clientapplications, and/or database service subscribers).

In the example illustrated in FIG. 4, storage system server node 430includes data page(s) 433, segment redo log(s) 435, segment managementfunctions 437, and attached SSDs 471-478. Again note that the label“SSD” may or may not refer to a solid-state drive, but may moregenerally refer to a local block storage volume, regardless of itsunderlying hardware. Similarly, storage system server node 440 includesdata page(s) 443, segment redo log(s) 445, segment management functions447, and attached SSDs 481-488; and storage system server node 450includes data page(s) 453, segment redo log(s) 455, segment managementfunctions 457, and attached SSDs 491-498.

As previously noted, in some embodiments, a sector is the unit ofalignment on an SSD and may be the maximum size on an SSD that can bewritten without the risk that the write will only be partiallycompleted. For example, the sector size for various solid-state drivesand spinning media may be 4 KB. In some embodiments of the distributeddatabase-optimized storage systems described herein, each and everysector may include have a 64-bit (8 byte) CRC at the beginning of thesector, regardless of the higher-level entity of which the sector is apart. In such embodiments, this CRC (which may be validated every time asector is read from SSD) may be used in detecting corruptions. In someembodiments, each and every sector may also include a “sector type” bytewhose value identifies the sector as a log sector, a data sector, or anuninitialized sector. For example, in some embodiments, a sector typebyte value of 0 may indicate that the sector is uninitialized.

One embodiment of a method for accessing data in a database system thatincludes a database engine and a separate distributed database storageservice, such as those described herein, is illustrated by the flowdiagram in FIG. 5. As illustrated at 510, in this example, the methodmay include a database engine head node receiving (e.g., from a databaseclient) a write request directed to a data record in a database table.For example, the write request may specify that a new data record shouldbe added to the database table (or to a particular data page thereof) ormay specify a modification to an existing data record in a particulardata page of the database table. The method may include the databaseengine head node generating a redo log record specifying the requestedwrite, as in 520, and sending the redo log record (but not theparticular data page to which the request is directed) to a node (ornodes) of a distributed database-optimized storage system that storesthe particular data page, as in 530. As previously noted, this mayinclude sending the redo log record to a node (or nodes) on which thedata page is replicated locally (e.g., within the same availability zoneor region) and/or a node (or nodes) in multiple or differentavailability zones or regions (e.g., an availability zone other than theone in which the database engine head node is implemented), in differentembodiments.

As illustrated in this example, the method may include, in response toreceiving the redo log record, the storage system node(s) writing theredo log record to disk (or to another type of persistent storagemedia), and returning a write acknowledgment to the database engine headnode, as in 540. In some embodiments, in response to receiving the writeacknowledgement(s), the database engine head node may return acorresponding write acknowledgement to the client from whom the writerequest was received (not shown). As illustrated in this example, atsome point in time (e.g., at a point in time subsequent to receiving theredo log record and returning the write acknowledgement), the method mayinclude the storage system node(s) coalescing multiple redo log recordsfor the particular data page (including, for example, the redo logrecord that was written to disk at step 540) to generate aninstantiation of the particular data page in its current state, as in550. For example, coalescing the redo log may include applying to apreviously instantiated version of the particular data page all of theredo logs that have been received by the storage system for theparticular data page but that have not yet been applied to an instanceof the particular data page to provide an up-to-date version of theparticular data page. Note that in some embodiments, an up-to-dateversion of the particular data page may be generated directly from oneor more redo logs, e.g., without applying them to a previously storedversion of the particular data page.

As illustrated in FIG. 5, the method may also include (e.g., at somepoint subsequent to coalescing redo logs to create an up-to-date versionof the particular data page) the database engine head node receiving aread request directed to the particular data page, as in 560. Inresponse, the database engine head node may send a corresponding readrequest to a storage node that stores the particular data page (e.g.,one of the storage nodes in the primary AZ or one in a secondary AZ), asin 570. Note that, in this example, it is assumed that the databaseengine head node does not store a current version of the particular datapage in its cache. Otherwise, the method may include database enginehead node responding to the read request itself (e.g., by returning therequested data from its cache), rather than sending a corresponding readrequest to one of the storage system nodes. As illustrated in thisexample, the method may include the storage system node to which therequest was sent returning the particular data page to the databaseengine head node in its current state, as in 580, after which thedatabase engine head node may return the requested data to the clientfrom whom the read request was received, as in 590.

In various embodiments, the version of the particular data page that isreturned to the database engine head node (e.g., in step 580) may be thesame version that was generated by the coalescing operation in step 550,or may be a more recent version that was created by a subsequentcoalescing operation (e.g., one that applied additional redo log recordsthat were subsequent to the coalescing operation in step 550). Forexample, an additional coalescing operation may have been performed atthe storage system node(s) in response to the receipt of the readrequest from the database engine head node, as part of a database crashrecovery operation, or in response to another type of trigger, indifferent embodiments. Note that in some embodiments, the operationsillustrated in FIG. 5 for accessing data in a database system thatincludes a database engine and a separate distributed database storageservice may be performed automatically (e.g., without user intervention)in the database system in response to receiving a request to access thedata.

In some embodiments, each of the storage system server nodes in thedistributed database-optimized storage system may implement a set ofprocesses running on the node server's operating system that managecommunication with the database engine head node, e.g., to receive redologs, send back data pages, etc. In some embodiments, all data blockswritten to the distributed database-optimized storage system may bebacked up to long-term and/or archival storage (e.g., in a remotekey-value durable backup storage system).

FIG. 6 is a block diagram illustrating the use of a separate distributeddatabase-optimized storage system in a database system, according to oneembodiment. In this example, one or more client processes 610 may storedata to one or more database tables maintained by a database system thatincludes a database engine 620 and a distributed database-optimizedstorage system 630. In the example illustrated in FIG. 6, databaseengine 620 includes database tier components 660 and client-side driver640 (which serves as the interface between distributeddatabase-optimized storage system 630 and database tier components 660).In some embodiments, database tier components 660 may perform functionssuch as those performed by query parsing, optimization and executioncomponent 305 and transaction and consistency management component 330of FIG. 3, and/or may store data pages, transaction logs and/or undologs (such as those stored by data page cache 335, transaction log 340and undo log 345 of FIG. 3).

In this example, one or more client processes 610 may send databasequery requests 615 (which may include read and/or write requeststargeting data stored on one or more of the storage nodes 635 a-635 n)to database tier components 660, and may receive database queryresponses 617 from database tier components 660 (e.g., responses thatinclude write acknowledgements and/or requested data). Each databasequery request 615 that includes a request to write to a data page may beparsed and optimized to generate one or more write record requests 641,which may be sent to client-side driver 640 for subsequent routing todistributed database-optimized storage system 630. In this example,client-side driver 640 may generate one or more redo log records 631corresponding to each write record request 641, and may send them tospecific ones of the storage nodes 635 of distributed database-optimizedstorage system 630. Distributed database-optimized storage system 630may return a corresponding write acknowledgement 623 for each redo logrecord 631 to database engine 620 (specifically to client-side driver640). Client-side driver 640 may pass these write acknowledgements todatabase tier components 660 (as write responses 642), which may thensend corresponding responses (e.g., write acknowledgements) to one ormore client processes 610 as one of database query responses 617.

In this example, each database query request 615 that includes a requestto read a data page may be parsed and optimized to generate one or moreread record requests 643, which may be sent to clients-side driver 640for subsequent routing to distributed database-optimized storage system630. In this example, client-side driver 640 may send these requests tospecific ones of the storage nodes 635 of distributed database-optimizedstorage system 630, and distributed database-optimized storage system630 may return the requested data pages 633 to database engine 620(specifically to client-side driver 640). Client-side driver 640 maysend the returned data pages to the database tier components 660 asreturn data records 644, and database tier components 660 may then sendthe data pages to one or more client processes 610 as database queryresponses 617.

In some embodiments, various error and/or data loss messages 634 may besent from distributed database-optimized storage system 630 to databaseengine 620 (specifically to client-side driver 640). These messages maybe passed from client-side driver 640 to database tier components 660 aserror and/or loss reporting messages 645, and then to one or more clientprocesses 610 along with (or instead of) a database query response 617.

In some embodiments, the APIs 631-634 of distributed database-optimizedstorage system 630 and the APIs 641-645 of client-side driver 640 mayexpose the functionality of the distributed database-optimized storagesystem 630 to database engine 620 as if database engine 620 were aclient of distributed database-optimized storage system 630. Forexample, database engine 620 (through client-side driver 640) may writeredo log records or request data pages through these APIs to perform (orfacilitate the performance of) various operations of the database systemimplemented by the combination of database engine 620 and distributeddatabase-optimized storage system 630 (e.g., storage, access, changelogging, recovery, and/or space management operations). As illustratedin FIG. 6, distributed database-optimized storage system 630 may storedata blocks on storage nodes 635 a-635 n, each of which may havemultiple attached SSDs. In some embodiments, distributeddatabase-optimized storage system 630 may provide high durability forstored data blocks through the application of various types ofredundancy schemes, including those that are deployed across multipleavailability zones and/or those in which contingency resource instancesare designated for use in the case of node-specific or AZ-wide failuresor other trigger conditions warranting the activation of the contingencyresource instances.

Note that in various embodiments, the API calls and responses betweendatabase engine 620 and distributed database-optimized storage system630 (e.g., APIs 631-634) and/or the API calls and responses betweenclient-side driver 640 and database tier components 660 (e.g., APIs641-645) in FIG. 6 may be performed over a secure proxy connection(e.g., one managed by a gateway control plane), or may be performed overthe public network or, alternatively, over a private channel such as avirtual private network (VPN) connection. These and other APIs to and/orbetween components of the database systems described herein may beimplemented according to different technologies, including, but notlimited to, Simple Object Access Protocol (SOAP) technology andRepresentational state transfer (REST) technology. For example, theseAPIs may be, but are not necessarily, implemented as SOAP APIs orRESTful APIs. SOAP is a protocol for exchanging information in thecontext of Web-based services. REST is an architectural style fordistributed hypermedia systems. A RESTful API (which may also bereferred to as a RESTful web service) is a web service API implementedusing HTTP and REST technology. The APIs described herein may in someembodiments be wrapped with client libraries in various languages,including, but not limited to, C, C++, Java, C# and Perl to supportintegration with database engine 620 and/or distributeddatabase-optimized storage system 630.

As noted above, in some embodiments, the functional components of adatabase system may be partitioned between those that are performed bythe database engine and those that are performed in a separate,distributed, database-optimized storage system. In one specific example,in response to receiving a request from a client process (or a threadthereof) to insert something into a database table (e.g., to update asingle data block by adding a record to that data block), one or morecomponents of the database engine head node may perform query parsing,optimization, and execution, and may send each portion of the query to atransaction and consistency management component. The transaction andconsistency management component may ensure that no other client process(or thread thereof) is trying to modify the same row at the same time.For example, the transaction and consistency management component may beresponsible for ensuring that this change is performed atomically,consistently, durably, and in an isolated manner in the database. Forexample, the transaction and consistency management component may worktogether with the client-side storage service driver of the databaseengine head node to generate a redo log record to be sent to one of thenodes in the distributed database-optimized storage service and to sendit to the distributed database-optimized storage service (along withother redo logs generated in response to other client requests) in anorder and/or with timing that ensures the ACID properties are met forthis transaction. Upon receiving the redo log record (which may beconsidered an “update record” by the storage service), the correspondingstorage node may update the data block, and may update a redo log forthe data block (e.g., a record of all changes directed to the datablock). In some embodiments, the database engine may be responsible forgenerating an undo log record for this change, and may also beresponsible for generating a redo log record for the undo log, both ofwhich may be used locally (in the database tier) for ensuringtransactionality. However, unlike in traditional database systems, thesystems described herein may shift the responsibility for applyingchanges to data blocks to the storage system (rather than applying themat the database tier and shipping the modified data blocks to thestorage system).

One embodiment of a method for performing a write operation in adatabase system, from the perspective of the database engine, isillustrated by the flow diagram in FIG. 7. As illustrated at 710, inthis example, the method may include the database engine head nodereceiving (e.g., from a database client) a write request directed to adata record in a database table. For example, the write request mayspecify that a new data record should be added to the database table (orto a particular data page thereof) or may specify a modification to anexisting data record in a particular data page of the database table.The method may also include the database engine head node (or aparticular component thereof) parsing and/or optimizing the writerequest, as in 720. For example, in some embodiments, the databaseengine head node may be responsible for generating a query executionplan. As illustrated in FIG. 7, the method may include the databaseengine head node generating a redo log record specifying the requestedwrite, as in 730, and the database engine head node (or, morespecifically, a client-side storage service driver on the databaseengine head node) determining the node of a distributeddatabase-optimized storage system that stores the particular data pageto which the write request is directed, as in 740.

As illustrated in this example, the method may include the databaseengine head node (or, more specifically, the client-side storage servicedriver on the database engine head node) sending the redo log record,but not any version of the particular data page, to the determined nodeof storage system, as in 750. As illustrated in FIG. 7, there may be noother action taken by the database engine head node with respect to thewrite request until (and unless) the database engine head node (or, morespecifically, the client-side storage service driver on the databaseengine head node) receives an acknowledgment of the write from thestorage system. Once this acknowledgement is received (shown as thepositive exit from 760), the method may include the database engine headnode returning a corresponding write acknowledgment to the requestor(e.g., to the client from whom the write request was received), as in770. Note that in some embodiments, if a write acknowledgement is notreceived from the storage system within a pre-determined time period,the database engine head node (or, more specifically, the client-sidestorage service driver on the database engine head node) may beconfigured to determine that the determined storage node has failed (oris degraded) or that some other error condition exists in the storagesystem. Note also that the operations illustrated in FIG. 7 forperforming a write operation may be performed automatically (e.g.,without user intervention) in the database system in response toreceiving a write request.

One embodiment of a method for performing a write operation in adatabase system, from the perspective of a distributeddatabase-optimized storage system, is illustrated by the flow diagram inFIG. 8. As illustrated at 810, in this example, the method may include anode of a distributed database-optimized storage system (e.g., a storagesystem server node in a primary or secondary AZ) receiving a redo logrecord that is directed to a particular data page that the node stores(but not any version of the particular data page itself) from a databaseengine (e.g., from a client-side storage service driver of a databasehead node), or from another client of the storage system. In response toreceiving the redo log record, the method may include the storage systemnode writing the redo log record for the page to one or more disks (orto another type of persistent storage media), as in 820. For example,the storage system node may append the redo log record to a redo log forthe particular data page that is stored on a particular disk, or to anyof a number of replicas of such a redo log that are stored on one ormore disks in the same availability zone or in each of two or moredifferent availability zones, in different embodiments. Once one or morecopies of the redo log record have been successfully written (accordingto a system-wide, application-specific, or client-specified durabilitypolicy), the method may also include the storage system node returning awrite acknowledgment to the database engine (or other client of thestorage system) as in 830. Note that the storage system node may returnthe write acknowledgement to the database engine at any time aftersuccessfully writing the redo log record, regardless of whether or notthe redo log record has been applied to a previously instantiatedversion of the particular data page to which it is directed on thestorage system node yet.

As illustrated in this example, if it is time for the storage systemnode to coalesce one or more redo log records for the particular datapage to create an up-to-date version of the particular data page (shownas the positive exit from 840), the method may include the storagesystem node applying one or more redo log records to the most recentlystored version of the particular data page to generate a new version ofthe particular data page in its current state, and writing that newversion of the particular data page to one or more disks (as in 850).For example, the coalesce operation may include the application of allredo log records that were received since the last coalesce operation(and/or that have not yet been applied to any version of the particulardata page) to the most recently instantiated version of the particulardata page. In other embodiments, a current version of the particulardata page may be generated directly from one or more redo logs, e.g.,without applying them to a previously stored version of the particulardata page. As described herein, there may be a variety of ways todetermine when it is time to coalesce pending redo log records for agiven data page, in different embodiments. For example, a coalesceoperation may be triggered for a data page at regular (e.g., periodic)time intervals, in response to receiving a single redo log targeting thedata page, in response to having received a pre-determined number ofredo log records targeting the data page or a pre-determined number ofredo log records targeting the data page within a given time period, inresponse to receiving a read request targeting the data page, inresponse to the initiation of a crash recovery operation, or accordingto any other suitable policy.

As illustrated in FIG. 8, if it is not time for the storage system nodeto coalesce redo log records for the particular data page (shown as thenegative exit from 840), but another redo log record targeting theparticular data page is received (shown as the positive exit from 860),the method may include repeating the operations illustrated at 820-860for the additional redo log record. In this example, as more redo logrecords targeting the particular data page are received by the storagesystem, the storage system node may repeat the operations illustrated at820-860 for each additional redo log record, and the storage system nodemay coalesce the redo log records for the particular data page from timeto time, according to one or more applicable triggers and/or policies.This is illustrated in FIG. 8 by the feedback from the positive exit of860 to 820, and the feedback from the negative exit of 860 to 840. Notethat the operations illustrated in FIG. 8 for performing a writeoperation may be performed automatically (e.g., without userintervention) in the storage system in response to receiving a redo logrecord.

Note that, in some embodiments, some data pages (e.g., data pages thatare rarely, if ever, accessed) may never be generated (e.g., through acoalesce operation) and/or persisted in memory. For example, in someembodiments, any redo log records directed to such data pages may bestored (e.g., persisted in memory) by one or more storage system nodes,but these redo log records may not be used to generate a completeversion of those data pages until or unless a request to read them isreceived. In such embodiments, even if a version of such a data page isgenerated (e.g., in response to a read request), it may not be persistedin memory (e.g., if it is unlikely to be accessed again soon, often, orever), but instead may be discarded at any point after it is returned tothe requestor.

One embodiment of a method for performing a read operation in a databasesystem, from the perspective of the database engine, is illustrated bythe flow diagram in FIG. 9. As illustrated at 910, in this example, themethod may include the database engine head node receiving (e.g., from adatabase client), a read request directed to a particular data page. Themethod may also include the database engine head node (or a particularcomponent thereof) parsing and/or optimizing the read request, as in920. For example, in some embodiments, the database engine head node maybe responsible for generating a query execution plan. As illustrated inFIG. 9, if the particular data page is resident in the cache of thedatabase engine head node, shown as the positive exit from 930, themethod may include the database engine head node returning the requesteddata from the version of the particular data page found in its cache, asin 935. For example, in some embodiments, the database engine head nodemay temporality hold copies of the most recently accessed data pages inits cache, and may update those copies in response to receiving writerequests directed to them (e.g., in addition to generating and passingredo log records for those write requests to a distributeddatabase-optimized storage system). In some such embodiments, if aparticular data page targeted by a read operation is resident in thecache, it may be assumed to be an up-to-date version of the particulardata page (e.g., it may be assumed that all redo log records targetingthe data page have already been applied to the version of the particulardata page that is stored in the cache).

As illustrated in FIG. 9, if the particular data page is not resident inthe cache of the database engine head node, shown as the negative exitfrom 930, the method may include the database engine head node (or, morespecifically, a client-side storage service driver on the databaseengine head node) determining a node in a distributed database-optimizedstorage system that stores the particular data page, and sending acorresponding read request to the determined storage system node, as in940. As illustrated in FIG. 9, there may be no other action taken by thedatabase engine head node with respect to the read request until (andunless) the database engine head node (or, more specifically, theclient-side storage service driver on the database engine head node)receives the particular data page (in its current state) from thestorage system. Once the database engine head node (or, morespecifically, the client-side storage service driver on the databaseengine head node) receives the particular data page in its current statefrom the determined storage system node (shown as the positive exit from950), the method may include the database engine head node returning therequested data to the requestor (e.g., the client from whom the readrequest was received), as in 960. For example, if the version of theparticular data page received from the determined storage system node isa version of the particular data page to which all redo log recordstargeting the particular data page to date have been applied (or atleast all of the redo log records that could be applied whilemaintaining the transactionality and consistency properties of thedatabase system), the database engine head node may return the requesteddata from the version of the particular data page received from thedetermined storage system node. Note that in some embodiments, if acurrent copy of the particular data page is not received from thestorage system within a pre-determined time period, the database enginehead node (or, more specifically, the client-side storage service driveron the database engine head node) may be configured to determine thatthe determined storage node has failed (or is degraded) or that someother error condition exists in the storage system. Note also that theoperations illustrated in FIG. 9 for performing a read operation may beperformed automatically (e.g., without user intervention) in thedatabase system in response to receiving a read request.

One embodiment of a method for performing a read operation in a databasesystem, from the perspective of a distributed database-optimized storagesystem, is illustrated by the flow diagram in FIG. 10. As illustrated at1010, in this example, the method may include a node in a distributeddatabase-optimized storage system receiving a read request directed to aparticular data page that is stored by the storage system node. Indifferent embodiments, the storage system may receive the read requestfrom a database engine (e.g., from a client-side storage service driverof a database head node), or from another storage service client. Asillustrated in this example, if the storage system node stores anup-to-date copy of the data page (shown as the positive exit from 1020),the method may include the storage system node returning the up-to-datecopy of the data page that it already stores, as in 1050. For example,if all of the redo log records targeting the particular block that havebeen received by the storage system node to date (or at least all of theredo log records that could be applied while maintaining thetransactionality and consistency properties of the database system) havebeen applied to the particular data page (e.g., if they have beencoalesced to create a current version of the particular data page), thestorage system node may not need to perform an additional coalesceoperation on the redo log records for the particular data page beforereturning a response.

On the other hand, if the storage system node does not store anup-to-date copy of the data page (shown as the negative exit from 1020),the method may include the storage system node retrieving the mostrecently stored copy of the particular data page from disk or fromanother persistent storage device, as in 1030, and then applying changesspecified in one or more redo log records for the particular data pageto the retrieved copy of the particular data page to generate anup-to-date copy of the particular data page, as in 1040. For example,the storage system node may apply to the retrieved copy of theparticular data page any and all redo log records targeting theparticular data page that have been received by the storage system nodeto date, but that have not yet been applied to the particular data page.Once the storage system node has created the up-to-date copy of theparticular data page, the storage system node may return the newlycreated copy of the particular data page to the database engine (orother storage system client) as the up-to-date copy of the data page (asin 1050). Note that the operations illustrated in FIG. 10 for performinga read operation may be performed automatically (e.g., without userintervention) in the storage system in response to receiving a readrequest.

As previously noted, a protection group (PG) is an abstract distributedentity that represents a unit of durability formed by a collection ofsegments. In some embodiments, a protection group may represent one ormore extents within a volume. A protection group may expose interfacesfor one or more extents, and may encapsulate (and hide) one or moresegments and associated metadata. The protection group may beresponsible for maintaining durability of the extents that it exposes,according to durability policy configured for the protection group. Insome embodiments, a protection group may achieve durability of all ofits constituent extents by using redundant segments to persist extentdata, and by actively maintaining such redundancy. The way in which theprotection group maps extent read/write operations onto the underlyingsegments may be opaque to the users of the extents. Different redundancystrategies may be employed in different embodiments, including, but notlimited to extent mirroring, extent erasure coding, and/or lazyreplication.

A “mirrored protection group” is a protection group in which each of theconstituent segments is a synchronous mirrored copy of a single extent.In this model, a change is considered durable if it has been madedurable on all affected synchronous mirrored segments within theprotection group. Protection groups may be formed within a singleavailability zone or across multiple availability zones. For example,for a protection group that encapsulates only segments within aparticular availability zone, the availability of the protection groupmay be tied directly to availability of the associated availabilityzone. In some embodiments, a regional protection group may encapsulatesegments across multiple availability zones. In some such embodiments,the regional protection group may be implemented as a collection ofcorresponding AZ Protection Groups, one from each AZ.

One embodiment of a method for performing read and write operations in adistributed database-optimized storage system that includes protectiongroups is illustrated by the flow diagram in FIG. 11. As illustrated at1110, in this example, the method may include a database engine headnode of a database tier receiving (e.g., from a database client) a writerequest directed to a data record in a database table. For example, thewrite request may specify that a new data record should be added to thedatabase table (or to a particular data page thereof) or may specify amodification to an existing data record in a particular data page of thedatabase table. In response to receiving the write request, the methodmay include the database engine head node (or, more specifically, aclient-side storage service driver on the database engine head node)sending a redo log record (but not a copy of the particular data page towhich the write request is directed) to two or more storage nodes in aprotection group of a distributed database-optimized storage system thatstore the particular data page to which the request is directed, as in1120.

As illustrated in this example, until the database engine head node (or,more specifically, the client-side storage service driver on thedatabase engine head node) receives an acknowledgement that the writewas successfully completed from a quorum of the storage nodes in theprotection group, the database engine head node may wait to receive awrite acknowledgement from a quorum of the storage nodes in theprotection group. This is illustrated in FIG. 11 by the feedback fromthe negative exit from 1130 to the input to 1130. Once the databaseengine head node has received a write acknowledgement from a quorum ofthe storage nodes in the protection group (shown as the positive exitfrom 1130), the method may include the database engine head nodereturning a corresponding write acknowledgement to the requestor (e.g.,to the database client), as in 1140. Note that in some embodiments, if awrite acknowledgement is not received from a quorum of the storage nodesin the protection group within a pre-determined time period, thedatabase engine head node (or, more specifically, the client-sidestorage service driver on the database engine head node) may beconfigured to determine that one or more of the storage nodes in theprotection group have failed (or are degraded) or that some other errorcondition exists in the storage system.

As illustrated in FIG. 11, the method may include (e.g., at some pointin time subsequent to receiving and responding to the write request),the database engine head node (or, more specifically, the client-sidestorage service driver on the database engine head node) receiving aread request directed to the particular data page (as in 1150). Inresponse to receiving the read request, the method may include thedatabase engine head node (or, more specifically, the client-sidestorage service driver on the database engine head node) sending a readrequest to two or more storage nodes in the protection group that storethe particular data page (as in 1160).

As illustrated in this example, until the database engine head node (or,more specifically, the client-side storage service driver on thedatabase engine head node) receives a current copy of the particulardata page from a quorum of the storage nodes in the protection group,the database engine head node may wait to receive a current copy of theparticular data page from a quorum of the storage nodes in theprotection group. For example, in some embodiments, one or more of thestorage nodes in the protection group may not store a current copy ofthe particular data page and may have to create a current copy of theparticular data page by applying one or more pending redo log records toan earlier version of the particular data page (e.g., in a coalesceoperation) before responding. This is illustrated in FIG. 11 by thefeedback from the negative exit from 1170 to the input to 1170. Once thedatabase engine head node has received a current copy of the particulardata page from a quorum of the storage nodes in the protection group(shown as the positive exit from 1170), the method may include thedatabase engine head node returning a current copy of the data page tothe requestor (e.g., to the database client), as in 1180. Note that insome embodiments, if a current copy of the particular data page is notreceived from a quorum of the storage nodes in the protection groupwithin a pre-determined time period, the database engine head node (or,more specifically, the client-side storage service driver on thedatabase engine head node) may be configured to determine that one ormore of the storage nodes in the protection group have failed (or aredegraded) or that some other error condition exists in the storagesystem. Note also that the operations illustrated in FIG. 11 forperforming write operations or for performing read operations may beperformed automatically (e.g., without user intervention) in thedatabase system in response to receiving requests to do so.

Some existing database systems flush all data pages to disk periodically(e.g., checkpointing all of the pages once every 5 minutes). In suchsystems, if there is a crash, the system might have to replay a largenumber of redo log records to re-create the current version of a datapage to which a lot of changes were directed since the last time thatdata page was flushed. For example, this may be the case for a hot datapage in the cache to which large numbers of changes are continuouslydirected, such as a page in which a sequence number is incremented eachtime an incoming order is received in an e-commerce application. Insteadof checkpointing all data pages stored in the system at one time, in thesystems described herein, checkpointing may be performed on a data block(e.g., data page) basis, rather than on a database or segment basis. Forexample, in some embodiments, checkpointing may be performed at eachstorage node, and each of the data pages stored on a particular storagenode may be coalesced to create a new version of data page (e.g., acheckpoint of that data page) on the storage node only when it iswarranted (e.g., when the number of redo log records its own redo logreaches a pre-determined number). In such embodiments, the database tiermay not be involved in checkpointing at all. Instead, checkpointing maybe a distributed process (e.g., a background process) that is theresponsibility of the storage nodes themselves. Note that becausecheckpointing may be performed by a background process on the storagetier (which may have visibility into other foreground and/or backgroundactivities affecting each storage node), in some embodiments, thestorage tier (or one of the storage system server nodes thereof) may beconfigured to postpone a checkpointing operation for a particularstorage node if it is being heavily loaded by another foreground orbackground process. In some embodiments, postponing a checkpointingoperation may prevent checkpointing from adversely affecting foregroundlatency.

In some embodiments, various in-memory data structures (such as thosedescribed herein) may be needed for a segment to function. In someembodiments, these in-memory structures may be built up during startup(e.g., following a crash) by doing a full scan of all log pages. In someembodiments, periodic checkpoints of some of these in-memory datastructures may be performed to reduce startup time following a crash.

In some existing database systems, the database tier may need to writedata pages out to the storage layer at the same frequency at whichchanges are being received, otherwise, if the cache gets full of dirtiedpages that have not yet been written out to the storage layer, a pagemay have to be flushed in order to accept more changes, which introduceslatency into the system. By contrast, in the systems described herein,as long as the redo logs for a data page in the cache of the databaseengine head node have been passed to the distributed storage system (anda write acknowledgement has been received), the database tier may evictthe data page (which can be reconstructed by the storage layer at anytime) from its cache.

In some embodiments of the systems described herein, crash recovery,flashback, and point in time restore operations may not require thereplay of either redo or undo logs. Instead, they may include buildingan instance (e.g., building a database instance using reserved orcontingency resource instances), resetting the current volume LSN to theappropriate commit point, and restarting the database service.

The database systems described herein may in some embodiments be scaledto accommodate larger database tables and/or higher throughput than someexisting databases, without suffering some of the disadvantagesassociated with previous database scaling approaches (e.g.,disadvantages in terms of complexity and/or cost). For example, in someembodiments, there may be no practical limit to the volume size, andvolumes may be able to grow dynamically without loss of availability orchange in performance (e.g., by adding an additional protection group ofsegments). In addition, assuming write traffic is spread acrosssegments, IOPS may be made virtually unbounded. For example, in someembodiments, IOPS may be increased or decreased without impacting theperformance of the currently running database, with any necessaryrestriping being performed in the background while new writes areforwarded to the storage tier. In such embodiments, query performancemay be made predictable and consistent without the need to freeze IOtraffic during backup operations or re-mirroring. Instead, the storagetier may manage striping, mirroring and heat management, removing theseresponsibilities from the database tier or administrator.

As described herein, all writes in the storage tier may be made durableon persistent media before being acknowledged back to the database tier.This may prevent logical corruptions on large-scale power events, andmay remove the need to restore from backup, in such cases. In someembodiments, the only time a restore from backup is required may be inresponse to a customer error (e.g., the accidental deletion of a table,or similar).

In some embodiments, the database systems described above may beimplemented by a service provider that offers different types ofvirtualized computing, storage, and/or other network-accessiblefunctionality to clients (e.g., client applications, customers, orservice subscribers). For example, one such service provider may allowcustomers to reserve, lease, or purchase access to virtualized resourcesthat implement the functionality of the database engine head node, thestorage system server nodes, and/or other components of the databasesystems described above. In some embodiments, the virtualized resourcesmay be implemented as a pool of resource instances (e.g., computeinstances, storage instances, and/or other types of resource instances),some of which may be reserved or designated as contingency resources forimplementing the services when they are initialized and/or following afailure or detection of another trigger condition on behalf of theclients of the services (e.g., database service clients, storage serviceclients, or other virtual computing system service clients). In someembodiments, designating contingency resource capacity may involvesetting a parameter value indicating the number of resource instances ina pool of available resource instances that make up the contingencyresource capacity without identifying any specific resource instances ascontingency resource instances. In other embodiments, designatingcontingency resource capacity may include creating a pool (or sub-pool)of resource instances in which particular ones of the available resourceinstances are designated as contingency resource instances for aparticular service. In such embodiments, designating particular resourceinstances as contingency resource instances may facilitate the placementof those resource instances in particular placement groups and/or mayallow them to be implemented using specific types or classes of hardwareor on particular machines.

One embodiment of a system that is configured to provide network-basedservices to clients is illustrated by the block diagram in FIG. 12. Inthis example, the system 1200 includes a provider network 1210comprising a plurality of resource instances 1230, such as instances1230A, 1230B, 1230D, 1230E, 1230G and 1230H in one availability zone1220A, and instances 1230J, 1230K, 1230M, 1230N, 1230P, and 1230Q in adifferent availability zone 1220B. The various resource instances 1230in the different availability zones 1220 may be reserved and/orallocated for use by clients (or potential clients) such as client 1248Aand 1248B. In the illustrated embodiment, system 1200 includes aresource manager 1280, a pricing manager 1281, and an interface manager1282. In some embodiments, the functionality of the interface manager1282 may be implemented by a subcomponent of the resource manager 1280and/or a subcomponent of the pricing manager 1281. The interface manager1282 may in some embodiments implement one or more programmaticinterfaces allowing clients 1248 (e.g., clients 1248A and 1248B) tosearch for, browse, reserve and acquire resource instances 1230 toobtain various types of services, e.g., to run and/or access variousapplications. For example, interface manager 1282 may in someembodiments to configured to communicate with various client devices1260 (e.g., client devices 1260A, 1260B, and 1260C in client network1250A, or client devices 1260D, 1260E, and 1260F in client network1250B), on behalf of clients 1248A and 1248B, respectively.

In the illustrated embodiment, at a given point in time, some or all ofthe resource instances 1230 may be assigned to resource instance pools,such as reserved instance pools 1221A or 1221B, contingency instancepools 1223A or 1223B, available (spot) instance pool 1225, or one ormore other pool(s) 1227. In some embodiments, a given resource instancepool (such as the available instance pool 1225) may contain sub-pools.Each pool (or sub-pool) may have an associated pricing policy for itsinstances, as well as other properties such as interruptibility settingsfor the instances that happen to be assigned to the pool or sub-pool. Itis noted that the pools may represent logical collections oraggregations, so that, for example, the presence of two instances in thesame pool or sub-pool may not necessarily imply anything about thephysical location of the hardware used for the two instances. Forexample, although the instances 1230 illustrated in FIG. 12 are shown asbelonging to availability zones 1220, in other embodiments the providernetwork 1210 may be organized differently (e.g., in some embodimentsavailability zones may not be implemented). Availability zones 1220 maybe grouped into geographic regions (not shown in FIG. 12), in someembodiments. Instance pools may be implemented within availability zonesin some embodiments (e.g., each availability zone may have its ownreserved instance pool), while in other embodiments an instance pool orsub-pool may span multiple availability zones.

In some embodiments, the pricing manager 1281, which may exist as aseparate entity in some embodiments and may be incorporated as anelement of the resource manager 1280 in other embodiments, may beconfigured to determine pricing for the use of various instances 1230,and/or may obtain information (e.g., resource usage records orstatistics) from a variety of data sources to generate recommendationson the instances that a client 1248 should acquire or reserve. In someembodiments, the interface manager subcomponents of a pricing manager1281 (and/or the resource manager 1280) may implement one or moreprogrammatic interfaces to allow clients 1248 to specify one or morepreferences and/or optimization goals to serve as additional input forthe processes of determining pricing and/or resource instancerecommendations. In addition, the pricing and/or recommendations made bythe pricing manager 1281 may be dependent on various types of pricinginformation, such as past pricing trends for different types and sizesof resource instances, pricing constraints specified by clients 1248,anticipated future pricing trends extrapolated or estimated by thepricing manager, and so on. Some or all of the types of information usedby the pricing manager 1281 to determine pricing and/or to make itsrecommendations, and the types of information maintained by the resourcemanager for resource reservations, allocations and pricing, may bestored in a persistent store such as a resource management database1291, in some embodiments.

The resource instances 1230 of a provider network may be grouped intoclasses or categories based on several different dimensions in someembodiments, and the pricing policies associated with different classesmay differ. FIG. 13 illustrates an example resource instanceclassification approach in which instances are classified based (atleast in part) on the timing and/or duration of instance allocations,e.g., on when instances are requested by clients (or dedicated for theuse of clients) and when they are released or otherwise re-allocated.Three high-level types 1300 of resource instances are shown in FIG. 13:reserved instances 1310, contingency instances 1320, and spot instances1330, each with respective pricing policies 1315, 1325 and 1335. Inother embodiments, the provider network may employ more, fewer, ordifferent classifications for resource instances (which may includeon-demand instances, not shown). In one embodiment, a client may reservean instance for a fairly long time period (e.g., a one-year term or athree-year term) in accordance with the pricing policy 1315, by paying alow, one-time, upfront payment for the instance, and then paying a lowhourly rate for actual use of the instance at any desired times duringthe term of the reservation. Thus, the client may, by making thelong-term reservation, be assured that its reserved instance 1310 willbe available whenever it is needed.

In some embodiments, if a client does not wish to make a long-termreservation, the client may instead opt to use spot instances 1330. Forexample, the spot pricing policy 1335 may allow a client to specify themaximum hourly price that the client is willing to pay, and the resourcemanager 1280 may set a spot price for a given set of resource instances(spot instances 1330) dynamically based on the prices clients arewilling to pay and on the number of instances available to support thespot model. In this example, if a client's bid meets or exceeds thecurrent spot price, an instance 1330 may be allocated to the client. Ifthe spot price rises beyond the bid of the client using a spot instance1330 (e.g., if the client is outbid for that instance), access to theinstance by the client may be revoked (e.g., the instance may be shutdown, and may be reallocated for the use of another client).

In some embodiments, clients who request web-based services may specifythat at least some of the resource instances for implementing a givenservice (e.g., for storing copies of data or metadata) be deployedacross multiple storage devices, machines, computing nodes, and/oravailability zones (e.g., for durability and/or availability), or mayexplicitly request that redundant resource instance capacity be madeavailable to the given service in case of a failure or to supportanticipated growth or scaling. In response, the resource manager 1280may designate contingency resource instance capacity (but not reserve itfor the exclusive use of the given service) in the same availabilityzone(s) or in one or more availability zones other than those in whichreserved instance capacity is implemented for the given service. In suchembodiments, pricing (e.g., per instance) for designating resourceinstances as contingency resource instances may be lower than pricing(per instance) for reserving resource instances as primary instancecapacity (e.g., it may be priced at 50%-70% of the rate for equivalentreserved instance capacity, in some embodiments), according to acontingency resource instance pricing policy 1325. In some embodiments,the service provider may attempt to supplement the revenue generatedfrom these contingency resource instances (e.g., to recoup some of thecost of maintaining these resource instances on behalf of a client whilenot collecting as much money for them as for reserved resources) byoffering at least a portion of the contingency resource instancecapacity on the spot market.

In the case that any of the contingency resource instances are leased onthe spot market, they may be subject to the same pricing policy as thatapplied to other spot resource instances (e.g., spot instance pricingpolicy 1335) or may be subject to a different spot instance pricingpolicy (e.g., one specified as part of contingency resource instancepricing policy 1325). In some embodiments, contingency resourceinstances may be leased with the understanding that the leases areinterruptible. In other words, any leases for contingency resourcesobtained on the spot market may be revoked at any time if they areneeded (for any of a variety of reasons) for the use of a service onwhose behalf they were designated as contingency resources, or may berevoked in response to the spot price rising beyond the bid of theclient who has leased them. In various embodiments, contingency resourceinstances that are activated or instantiated for the use of the serviceson whose behalf they were so designated may be subject to the samepricing policy as that applied to the resource instances that wereoriginally reserved for those services (e.g., reserved instance pricingpolicy 1315) or may be subject to a different reserved instance pricingpolicy (e.g., one specified as part of contingency resource instancepricing policy 1325). In some embodiments, contingency instance pricingpolicy 1325 may specify pricing for designating resource instances ascontingency resource instances, pricing for activating those contingencyresource instances by the services on whose behalf they are sodesignated (e.g., when activating them as additional resource instancecapacity and/or as replacement resource instance capacity), and/or aminimum bid price at which they may be leased on the spot market.

The prices of reserved instances 1310, contingency instances 1320, andspot instances 1335 may also vary based on the availability zones 1220and/or geographic regions in which the instances are located. Forexample, the operator of provider network 1210 may have had to paydifferent costs for setting up data centers in different physicallocations, and may have to pay varying location-dependent ongoing costsfor infrastructure and maintenance services such as networkconnectivity, cooling and so on, which may result in different pricingpolicies for different availability zones and/or regions. Fluctuationsin supply and demand may also result in time-varying prices for thedifferent types of instances. In some embodiments, the price for a givenlong-term reservation may typically remain unchanged once a clientcompletes the reservation. In some embodiments, pricing for reservedinstances 1310, contingency instances 1320, and/or spot instances 1335may also vary based on expected and/or actual uptime ratios. The uptimeratio of a particular instance may be defined as the ratio of the amountof time the instance is activated to the total amount of time for whichthe instance is reserved.

Instance pricing may also vary based on other factors, in differentembodiments. For example, in the case of compute instances, theperformance capacities of different CPUs and other components of computeservers such as memory size may affect the pricing for use of thecompute instances. In some embodiments, software features such asoperating systems, hypervisors, middleware stacks and the like may alsobe taken into account in determining the pricing policies associatedwith various instances. For both compute instances and storageinstances, storage device characteristics such as total storagecapacity, supported I/O rates and the like may be used to developpricing policies in some implementations. Pricing policies may also bedependent on networking capabilities and networking usage (e.g., numberof megabytes of data transferred, and/or the distances over whichnetwork traffic is transmitted). The various pricing policies, includingstatic and dynamic components of pricing, as well as location-dependentand location-independent components, may be used by pricing manager 1281to set prices and/or to make its recommendations. Some or all of thepricing information may be stored in resource management database 1291,and the pricing manager 1281 may retrieve the information from thedatabase as needed. In some embodiments, the resource instances of aprovider network may be organized as pools based on, for example, whichinstances are currently being used as spot instances (e.g., instances inpool 1225 of FIG. 12), which instances are reserved (e.g., instances inpools 1221A and 1221B), which instances are designated as contingencyinstances (e.g., instances in pools 1223A and 1223B), and so on.

One embodiment of a system that is configured to fulfill resourceinstance requests using reserved, contingency, and/or interruptible(spot) resource instances is illustrated by the block diagram in FIG.14. FIG. 14 illustrates an embodiment in which a resource manager 1450may fulfill requirements for the use of various resource instances(e.g., virtual compute resource instances, storage resource instances,database instances, etc.). In the illustrated embodiment, system 1400includes a plurality of instances 1435, each of which is assigned to aninstance pool. As shown in the example illustrated in FIG. 14, instances1435 that are currently active (e.g., accessible via the network,performing functions, running applications, and/or providing services tovarious clients 1480), which may be referred to as in-use instances1405, may include instances in several sub-pools, including a reservedinstances pool 1410, a contingency instance pool 1420, and one or moreinterruptible (or spot) instance pool(s) 1430. In the illustratedexample, reserved instance pool 1410 includes (at least) instances 1435Aand 1435B, which are reserved for the exclusive use of a particularservice, process, client and/or application.

In this example, contingency instance pool 1420 includes (at least)instances 1435C and 1435D. In this example, contingency instance 1435Chas been placed in reserved instance pool 1410 and activated for the useof a particular service, process, client and/or application on whosebehalf one or more resource instances were designated as contingencyresource instances (e.g., in response to a node-specific or AZ-widefailure, to support increased scaling of the service, to improveperformance, to replace one or more reserved resource instances involvedin a maintenance operation, or in response to another trigger conditionwarranting the activation of the contingency resources instance beingmet). In this example, resource instance 1435D has been placed ininterruptible (spot) instance pool 1430 and provided to a service,process, client and/or application other than one on whose behalfresource instances were designated as contingency resource instances onthe spot market (e.g., through an interruptible lease). In other words,the lease on resource instance 1435D may be revoked at any time and maybe placed in reserve instance pool 1410 for the use of a service,process, client and/or application on whose behalf one or more resourceinstances were designated as contingency resource instances (e.g., inresponse to a node-specific or AZ-wide failure, to support increasedscaling of the service, to improve performance, to replace one or morereserved resource instances involved in a maintenance operation, or inresponse to detection of another trigger condition). This is illustratedin FIG. 14 by the overlaps between the borders of reserved instance pool1410, contingency instance pool 1420, and interruptible (spot) instancepool 1430. In this example, interruptible (spot) instance pool 1430 alsoincludes (at least) instances 1435E and 1435F. While these resourceinstances may not have been designated as contingency resources for anyparticular services, processes, clients and/or applications, in someembodiments they be leased using an interruptible lease that can berevoked by the resource manager 1450 at any time (e.g., for the use ofhigher priority services/processes/clients/applications), according toany of a variety of applicable resource management policies.

In this example, instances that are currently not in use may be assignedto an available instance pool 1415. A subset of the instances of theavailable instance pool 1415 (e.g., instances 1435M-1435P) may beassigned to one or more sub-pools of unused contingency resourceinstances, such as unused contingency instance sub-pool 1425. Otherunused instances (e.g., instances 1435G-1435L) may be generallyavailable for use (e.g., through a spot market or on-demand). In someembodiments, instances may be moved in and out of the various pools andsub-pools illustrated in FIG. 14 in response to actual and/oranticipated supply and demand (e.g., for load or heat balancingpurposes) or to otherwise improve performance of a service (e.g., byimplementing one or more components of the service using differentcomputing nodes, underlying hardware, or other higher-performanceresources), in addition to being moved in response to a node-specific orAZ-wide failure, to support increased scaling of the service, to improveperformance, to replace one or more reserved resource instances involvedin a maintenance operation, or in response to another trigger conditionwarranting the activation of the contingency resources instance beingmet. In some embodiments, resource instances may be moved from thereserved instance pool 1410 to the usused contingency instance sub-pool1425 following the failure of a computing node on which the resourceinstance was implemented (e.g., in the case that a resource instancethat was temporarily unreachable has been replaced by a correspondingcontingency resource instance).

As illustrated in this example, system 1400 may also include a pricingmanager 1455. The pricing manager 1455 may be configured to determinepricing for the use of various instances 1435 and/or to generaterecommendations of instances to be used by clients 1480. As in theprevious example, a resource management database (not shown) may be usedto store various types of instance information, including pricinginformation, performance capacity information, usage records, and/orinterruptibility settings of various resources. It is noted thatalthough availability zones are not shown explicitly in FIG. 14, each ofthe instances shown may in some embodiments belong to an availabilityzone and/or a geographic region of a provider network. For example, allthe instances 1435 shown in FIG. 14 may belong to the same availabilityzone, or sub-sets of these instances may belong to differentavailability zones, in different embodiments.

As described earlier, clients 1480 may in some embodiments reserveresource instances for agreed-upon reservation periods such as one-yearterms or three-year terms. When a client 1480 makes such a reservation,the resource manager 1450 may be committed to provide access to aresource instance with the specified performance capability and othercharacteristics, whenever the client requests such access during theterm of the reservation. In some embodiments, a client may be able torequest that redundant instance capacity be maintained (or madeavailable in case of a node-specific or AZ-wide failure) in two or moreavailability zones on behalf of the client (e.g., resource instancecapacity that may take over in the case of a failure). In some suchembodiments, one or more resource instances in one or more availabilityzones may be reserved for the use of a client 1480 (e.g., reservedinstances 1435A or 1435B in reserved instance pool 1410). Additionalresource instances (e.g., resource instances in the same or otheravailability zones) may be designated as contingency instances that areto be activated for the use of the client only if and when they areneeded (e.g., to replace reserved resource instances in the case of afailover condition or while performing maintenance operations on one ormore nodes on which the reserved resource instances are implemented, toreplace or supplement reserved resource instances to improve performanceor to support additional scaling, or in response to one or more othertrigger conditions being met).

In the example illustrated in FIG. 14, instances 1435M-1435P (in unusedcontingency instance sub-pool 1425) may be resource instances that havebeen designated as contingency resources, but that have not yet beenactivated, while instances 1435C and 1435D may be resource instanceswere designated as contingency resources, and that have been activatedin response to any of a variety of trigger conditions being met. Asdescribed herein, in some embodiments, resource instances in the unusedcontingency instance sub-pool 1425 may be offered to clients 1480 on thespot market through interruptible leases, but these leases may berevoked at any time by the resource manager 1450.

In some embodiments, the pricing for interruptible (spot) instances(e.g., instances in the interruptible instances pool 1430 and/or anycontingency instances within contingency instance pool 1420 that havebeen leased to various clients on the spot market) may vary over time,depending for example on the relative demand for and supply of availableinstances. For example, when a client submits an acceptable instanceacquisition request for such an instance (e.g., if the client's bid forthe instance meets the current price for such instances), an instance ofthe requested type may be allocated to the client, and the instance maybe assigned to the in-use interruptible instance pool 1430. The totalnumber of available spot instances to be kept either as in reserve inthe available instance pool 1415, or in the in-use instance pools 1430,may be determined by the resource manager 1450, and may be based (atleast in part) on the number of reserved instances, contingencyinstances and spot instances that are in use at any given time, theactual or anticipated rate of requests for resource instances, or otherfactors. In the embodiment illustrated in FIG. 14, the resource manager1450 may maintain a buffer of instances in the available instance pool1415 specifically to meet current and/or anticipated instance requests.

In some embodiments, interruptible (spot) instances may allow clients tosave the state of applications and/or complete some critical work beforethese instances are interrupted or stopped. For example, in oneembodiment, the resource manager 1450 may support an interruptibilitysetting that gives a client a five-minute or thirty minute advancewarning before access to an interruptible (spot) instance is revoked. Inother embodiments (or for particular instances, such as contingencyinstances 1420 that have been leased to a client on the spot marketwhile they are not needed by the clients on whose behalf they weredesignated as contingency resources), leases for interruptible (spot)instances may be revoked at any time and/or without warning. In someembodiments, the pricing for instances that are interruptible withoutwarning may be different (e.g., lower) than the pricing for instancesthat are interruptible following a warning, and the length of thewarning period provided may vary at the granularity of a minute based onthe price the client is willing to pay, such that clients willing to payone amount may receive a five minute warning, while clients willing topay slightly more may receive ten minute warnings, and so on. In someimplementations, the current spot instance pricing rate may be set bythe pricing manager 1455 based (at least in part) on the current size ofvarious interruptible instance sub-pool(s), and/or on the total size ofthe available instance pool 1415. Spot pricing may also be dependent onthe expected rate of requests for spot instances, the expected rate ofinstance upgrade requests (e.g., requests to upgrade an instance frominterruptible to reserved), actual usage records, and/or other metrics.

As illustrated in this example, an interface manager 1460 may beresponsible for implementing functionality related to variousprogrammatic interfaces supporting interactions with the resourcemanager 1450 and/or pricing manager 1455, in some embodiments. In someembodiments, resource manager 1450 may be configured to move instancesin and out of various pools or sub-pools (e.g., from the availableinstance pool 1415 to the unused contingency instance sub-pool 1425 orto the spot instance sub-pool 1430 or reserved instance pool 1410 of thein-use instance pool 1405, from one of these pools back to the availableinstance pool 1415, or from the reserved instance pool 1410 of thein-use instance pool 1405 to the unused contingency instance sub-pool1425) based on current and/or projected supply and demand or in responseto various trigger conditions being met. The relative pricing for theresource instances may vary based on supply and demand and on theinstance pools in which each of the resource instances are assigned atany given time. For example, if the rate of requests for spot resourceinstances increases, in some embodiments the price and/or number ofinstances in the spot instance sub-pool 1430 may be increasedaccordingly, as long as the resource manager 1450 is still able tomaintain the available resource instances 1415 needed for anyoutstanding reservations (including any contingency resource instancesthat would be needed in the case of a contingency trigger conditionbeing met). The resource manager 1450 may thus be configured to balancea number of potentially competing demands when deciding how to size thevarious pools and sub-pools in some embodiments. In some cases, the sameclient 1480 may wish to utilize different types of pricing models and/orinterruptibility settings for different subsets of the client'sapplication set—e.g., such a client may use (or request the use of) anycombination of reserved instances, contingency instances, and/or spotinstances at various times and for various purposes.

In some embodiments, the resource manager 1450 may also support upgradesand/or downgrades of the instances allocated to a client 1480. E.g., aclient 1480 may be willing to pay a baseline pricing rate for a giveninstance for a period of time during which the instance is interruptible(e.g., according to an interruptible-with-warning orinterruptible-without-warning setting) and may be interested inupgrading the instance to reserved instance setting for an additionalprice for some period of time. Interruptibility downgrades (e.g., from areserved instance setting to an interruptible instance setting or froman interruptible-with-warning setting to aninterruptible-without-warning setting) may also be supported in someembodiments, and may be associated with a corresponding reduction inprice. In general, in some embodiments, the billing amount charged to aclient may be based at least in part on the pricing rates in effect forthe different levels of interruptibility of an instance while it wasallocated to the client and/or the respective durations for which theinstance's interruptibility was set to each of the levels. For example,if a client 1480 used an instance 1435 at interruptibility level I1 fora time period T1 during which the instance pricing for level I1 was P1,and the client used that same instance at interruptibility level I2 fora time period T2 during which the instance pricing for level I2 was P2,the billing amounts charged to the client for that instance may be basedat least in part on the sum of the products (T1*P1)+(T2*P2).

In some embodiments and for certain kinds of client applications, it maybe beneficial to manage and schedule resources at other granularities inaddition to, or instead of, entire resource instances. For example, insome embodiments, the resource manager 1450 may be configured todetermine a dynamically varying price per execution unit (expressed forexample in units such as CPU-seconds, CPU-minutes, CPU-hours, MegaFLOPs,Megahertz, Gigahertz and the like) of excess resource capacity, and usethe price to select client-provided applications for execution,according to at least some embodiments. A client 1480 may provide one ormore application packages to the resource manager 1450, e.g., with thehelp of a programmatic interface such as an API or a one or more webpages implemented by interface manager 1460, where each applicationpackage includes an executable object and has an associated pricingconstraint to be used to schedule the execution of the executableobject. For example, a client may provide an executable object that canbe deployed and run on a JVM that is compliant with a specified versionof the Java™ Development Kit (JDK), a platform that supports variousinterpreted or compiled programming languages such as Ruby, Python,Perl, C, C++ and the like, or on a high-performance computing executionplatform that conforms to one or more industry standards. The client1480 may indicate, as a pricing constraint, that it is willing to pay upto specified amount for each CPU-minute that the executable is run on anexecution platform with a specified performance capacity (e.g., on a JDK1.6 JVM running on CPU X at 3 GHz or higher clock rate). The applicationpackages provided by clients may be stored in an application repository1470, in some embodiments. Various other details regarding theapplication may also be specified by the client via the applicationpackage, such as input/output needs of the application; further detailsof application package contents are provided below.

In the illustrated embodiment, a subset of available instances (such asinstances 1435Q, 1435R, 1435S and 1435T) may represent excess resourcecapacity that is usable for the use of various application packages. Theresource manager 1450 may instantiate a number of execution platforms(EPs) 1440 on these instances, as needed, to satisfy the executionrequests for the application packages provided by the clients. Forexample, an EP 1140A may be instantiated on instance 1435Q, two EPs1440B and 1140C may be instantiated on instance 1435R, and one EP 1440Dmay span multiple instances, such as 1435S and 1435T. In variousembodiments, an execution platform may comprise any of a variety ofmiddleware entities or software collections that may be needed forexecution of client applications, such as JVMs, application serverinstances, database instances, special-purpose or general-purposeoperating systems, high-performance computing platforms such as genomeanalysis platforms, simulation test beds, map-reduce executionenvironments, and the like.

As illustrated in this example, a flexible mapping of executionplatforms to the excess resource capacity of a provider network may beimplemented, in some embodiments, such that a single EP 1440 may beinstantiated on one resource instance 1435, multiple EPs 1440 may beinstantiated on one resource instance 1435, or a single EP 1440 may beinstantiated on multiple resource instances 1435. In some embodiments,e.g., where a resource instance 1435 typically comprises a virtualcompute platform that relies on a hypervisor running on some“bare-metal” hardware asset, some of the bare-metal hardware assets maybe used for the excess resource capacity without instantiatinghypervisors or other components typically used for resource instances.Pricing per execution unit (e.g., per CPU-minute) for different types ofEPs may vary dynamically in some embodiments, based on factors such asthe supply and demand for such EPs, the performance capabilities of theEPs, the requirements of the resource manager to maintain availableinstances to support unfulfilled reservation slots, and so on.

In some embodiments, the resource manager 1450 may attempt to find a“best match” execution platform for various application packages usingone or more criteria. For example, in one embodiment, the resourcemanager 1450 may select a particular EP 1440 on which to scheduleexecution of the executable object of an application package based atleast in part on the current pricing of execution units of the EP 1440and the pricing constraints of the application package (e.g., themaximum price the client is willing to pay). If a match is found,execution of the client's application may be started (or resumed) on theselected EP 1440.

FIG. 15 is a block diagram illustrating an example application packagethat may be submitted by a client to a resource manager of anetwork-based service provider, according to one embodiment. Morespecifically, FIG. 15 illustrates example contents of an applicationpackage that may be submitted by a client 1580 to a resource manager1530. As illustrated in this example, an application package (AP) 1510Amay include an executable object 1512, such as a jar (Java™ archive)file, a war (web application archive) file, an ear (enterprise archive)file, an exe file, one or more scripts written in any appropriatelanguage such as Python, Ruby, Perl, any of various variants of SQL,shell scripts, and the like. In one implementation supporting parallelor multi-threaded application types, the executable object 1512 maycomprise one thread (or multiple threads) of a multi-threaded orparallel application. For example, several application packages 1510 maybe created for a single multi-threaded application, such that eachpackage 1510 specifies a subset of the complete set of threads of theapplication as the package's executable object 1512. In some embodimentsthe AP 1510A may include a set of preferred or required resourcespecifications 1514, such as a minimum CPU speed, CPU vendor orarchitecture details, minimum main memory requirements, an operatingsystem version, application server version, database management systemvendor and version, and so on. Some of the resource specifications maybe labeled as mandatory, i.e., the resource manager 1530 may be unableto execute the application if the mandatory requirements are not met.Non-mandatory resource specifications may serve as hints or advisoriesto the resource manager; e.g., the resource manager may in someimplementations make a best effort to find execution platforms that meetnon-mandatory specifications.

Some types of applications may have dependencies or constraints-forexample, one application may rely on an external web site beingavailable, or may perform better when an external web site is available.Another application may be configured to obtain work tasks or jobs froman external job queue, such that if the job queue is empty orunreachable the application may not be able to perform much useful work.As illustrated in this example, AP 1510A may contain indications of suchexecution constraints 1516, in some embodiments. A client 1580 mayinclude pricing constraints 1518 in the application package itself insome embodiments (e.g., the maximum price the client is willing to payper CPU-minute or per some other execution unit). In some embodiments,the client may specify pricing constraints for completing execution ofthe application, instead of or in addition to specifying the client'sbid per execution unit. Pricing constraints associated with anapplication package may be specified and/or stored separately from othercontents of the application package in some embodiments, e.g., anapplication package may not include the pricing constraints in somecases. A client 1580 may in some implementations update the bid or otherdetails of the pricing constraints 1518 as needed during the lifetime ofthe application. For example, if an application is suspended or stoppedbecause the prevailing price for using the application platform it needshas risen beyond the price bid by the client originally, the client maybe allowed to raise the bid; and if the client wishes to lower costs forsome reasons, the client may be allowed to lower the bid for one or moreof the client's application packages.

When resource manager 1580 receives an application package 1510, in someembodiments it may store the package in a persistent applicationrepository 1550. If a suitable execution platform can be found for theapplication submitted by the client, the execution of the application onthat selected EP (e.g., EP 1540) may be initiated. In some embodiments,the application package 1510 may only be stored if an EP cannotimmediately be found for it, i.e., an application package 1510 (such asAP 1510B or AP 1510C) may be stored in the application repository 1550only when and if the execution of the application cannot proceed. Insome embodiments, the resource manager 1530 may also store a persistentapplication state object (ASO) 1520 (such as a serialized Java™ objectfile, or any other object representation of the state of an applicationthat allows the resumption of the application when a suitable executionplatform become available) for each application object 1510 (e.g., ASO1520B for application package 1510B, ASO 1520C for application package1510C, and so on). For applications whose execution has not yet begun,the corresponding state representation object 1520 may be empty. Otherinformation not shown in FIG. 15 may be included in application packages1510 and/or in application repository 1550 in some embodiments. Forexample, one or more representation of execution metrics (e.g., how manyCPU-minutes of execution have been completed so far for theapplication), execution history (on which specific execution platformsthe application has been executed), and the like may be stored inapplication repository 1550, in some embodiments. In some embodiments,security constraints may also be associated with each applicationpackage 1510 (e.g., the client 1580 may encrypt portions of theapplication package and/or use a digital signature on portions of theapplication package). In such embodiments, the resource manager 1530 andthe client 1580 may need to transfer or exchange one or more keys toimplement the security mechanism being used.

As previously noted, in some embodiments of the database systemsdescribed herein (e.g., those that include a single database engine headnode in a database tier and a plurality of storage nodes in a separatedistributed database-optimized storage system), replication operationsmay involve moving redo log records, and not data blocks. Therefore, theperformance impact of replication may be lower than in other databasesystems. In addition, in such systems, coordination of writes acrossavailability zones may be performed at the storage tier and may notrequire the use of a reserved (standby) resource instances (e.g.,resource instances implementing additional database engine head node)for synchronous replication, which may reduce costs when compared withexisting database systems. For example, in some existing databasesystems, database tier functions are physically replicated on themultiple machines, which may be the same machines (or at least machinesin the same availability zones) as those on which storage node serverfunctionality for the database system is implemented (e.g., to managedata replication, as part of their normal configuration and operation),which may allow them to quickly recover from a node-specific or AZ-widefailure. In some existing distributed database systems, only a portionof the replicated database tier functionality that is provisioned (andreserved) in secondary AZs may actually be used in the secondary AZsduring normal operation. For example, the replicated database tiercomponents may receive write requests and write data to various storagedevices, but may not perform the other control functions of the givendatabase until or unless the replicated database tier components takeover these control functions from the corresponding components inanother AZ as part of a failover operation.

In some embodiments, however, the database systems described herein maynot require dedicated local resources in every AZ for interface andcontrol functions (e.g., the control plane of the database system)during normal operation (e.g., while the database engine head node isactive, the system is meeting performance expectations, etc.).Therefore, in some embodiments, rather than provisioning enough standbyresource instance capacity to implement an additional database enginehead node for a given database instance in one or more AZs other thanthe one in which the database engine head node is implemented, theservice provider may designate that amount of resource instance capacityin those AZs as contingency resource capacity for the given databaseinstance, but may allow that contingency resource capacity to be leasedto other services, clients, processes, or applications until and unlessit is needed to implement an additional or replacement database enginehead node for the given database.

In embodiments in which a client (e.g., a customer or subscriber who hasrequested database services) has specified that a given database bedeployed across multiple availability zones, the service provider mayprovision (and may reserve) resource instances for storage system servernodes (and corresponding storage devices) in multiple availabilityzones, but may only provision resource instance capacity for a databaseengine head node in one of those availability zones (or machinestherein). The service provider may designate additional resourceinstance capacity as contingency resource capacity for the givendatabase, but that resource capacity may not be reserved or activatedfor its use (e.g., by instantiating another database engine head node)unless it is needed due to a node-specific or AZ-wide failure, tosupport increased scaling of the service, to improve performance, toreplace one or more reserved resource instances involved in amaintenance operation, or in response to detection of or another triggercondition. Instead, while the database engine head node implemented bythe active, provisioned (and, in many cases, reserved) resource instancecapacity is operating normally (e.g., within its expected or desiredperformance targets), it (or more specifically, the client side driverof the database engine head node) may handle sending redo log records tothe storage system server nodes in all of the AZs. For example, inresponse to receiving write requests, the database engine head node maypass information about those requests (e.g., redo log records) to theclient side driver, and the client side driver may take responsibilityfor passing the redo log records to both local storage system servernodes that comprise the targeted volume (e.g., storage system nodes inthe same AZ) and any storage system server nodes that comprise thetargeted volume and that exist in another AZ, where all of those storagesystem server nodes form (at least part of) a protection group for thatsegment of data. In such systems, there may be no need to provision,instantiate and/or activate a database engine head node in the otherAZs, because the client side driver on the source database nodecommunicates with all of the storage system server nodes regardless ofwhether they are in the same AZ as the client side driver or in otherAZs.

As previously described, in some embodiments, in order to generaterevenue using what would otherwise be largely unused excess resourceinstance capacity, the systems described herein may be configured tooffer at least a portion of the contingency instance capacity in a givenAZ (e.g., an AZ that serves as a secondary AZ for a given database) onthe spot market.

In some embodiments, in the case of a failure of the computing node onwhich the database engine head node for a given database is implementeda computing node on which the database engine head node for a givendatabase (or an AZ-wide failure affecting the a computing node on whichthe database engine head node is implemented) for the given database, afailover process may be initiated in order to rebuild and restart thegiven database. In some embodiments, this failover process may include aresource manager component of the provider of the database servicerevoking the leases of one or more resource instances in another AZ thatwere designated as contingency resources for the given database, butthat have since been leased to another entity on the spot market. Inthis example, the other AZ may include all of the same data volumes thatwere maintained on behalf of the given database in the primary AZ (e.g.,these volumes may have been replicated on storage system server nodesand corresponding storage devices in the other AZ, as described herein).Therefore, in response to the failover of the given database, a newdatabase engine head node may be instantiated using the contingencyresource instance capacity on the other AZ, and, once activated, thatnew database engine head node may immediately have access to all of thedata that was committed to those data volumes prior to the failover.

In some embodiments, a control plane function of the database system (orthe provider of the database service) may monitor the activities of thedatabase system (e.g., periodically or in response to a detected errorcondition) to determine whether (at any given time) the database enginehead node is reachable. If not, the control plane function (or serviceprovider) may attempt to provision a new database engine head node andprovide a mechanism to direct new requests targeting the correspondingdatabase to the new database engine head node. The new database enginehead node may then attempt to connect to the volume on which the targetdata is located, and the storage system volume may attempt to open allof the storage system server nodes on which the data is (or was)located. If some of the storage system server nodes have failed or areotherwise unreachable, those storage system server nodes may be fencedout of the volume (at least temporarily) so that requests are notdirected to those nodes. If the fenced out nodes subsequently recover orbecome reachable, the storage system may be configured to restore themto the current state of the other replicas of that data. Note that insome embodiments, a similar failover process may be performed within asingle AZ. For example, if additional resource instance capacity (e.g.,either contingency resource capacity or other unused/undesignatedresource instance capacity) is available within the same AZ (e.g., ifthe failure of the computing node on which the database engine head nodewas implemented is not an AZ-wide failure), the control plane of thedatabase system (or service provider) may be configured to instantiateanother database engine head node on another computing node within thesame AZ and attach the new database engine head node to the new databaseengine head node, after which the failover process may be similar tothat described above for the multiple-AZ case.

One embodiment of a method for managing contingency resource instancecapacity by a scalable database service provider is illustrated by theflow diagram in FIG. 16. As illustrated at 1610, in this example, themethod may include a scalable database service provider instantiating adatabase engine head node for a given database table using one or morereserved resource instance(s), and designating contingency resourceinstance capacity (enough to be able to instantiate another databaseengine head node) in a different availability zone. In some embodiments,the service provider may also provision resource instances forinstantiating storage system server nodes in one or more availabilityzones (not shown). The method may include the service provider making atleast some of the contingency resource instance capacity available forlease on spot market, as in 1620. In other words, other services,clients, applications, or processes may be granted interruptible leasesfor contingency resource instances while they are not needed to providethe database services for which they were designated as contingencyresource instances. After the resource instances that implement thegiven database table are activated, the system may begin receiving andprocessing query requests that are directed to the database table(including read and write requests).

As illustrated in this example, the method may include the databaseengine head node receiving a read or write request directed to a datarecord in a database table, as in 1630. The database engine head nodemay then send information about the read or write request (e.g., a readquery or a redo log record) to a storage system server node that storesthe data page to which the request is directed, as in 1640. The methodmay include the server node receiving the information and then applyingthe write request or responding to the read request, as in 1650. Asdescribed in detail herein, in various embodiments, applying a writerequest may include (at some point) coalescing multiple redo log recordsto generate a current version of the targeted data page, and respondingto a read request may include returning requested data (which may alsoinclude coalescing multiple redo log records to generate a currentversion of the targeted data page prior to returning the requesteddata).

As illustrated in this example, if the database engine head node isoperating as expected, shown as the positive exit from 1660, the methodmay include repeating the operations illustrated as 1630-1650 to receiveand process one or more additional read or write requests. For example,while the database engine head node is active, and the performance ofthe system is acceptable (e.g., if it is meeting performanceexpectations with or without additional scaling), there may be no needto activate any of the contingency resource instance capacity for thegiven database table. However, once the database engine head node is nolonger operating as expected (shown as the negative exit from 1660), themethod may include the database service provider revoking any leases onthe contingency resource instance capacity (as in 1670), theninstantiating another database head node using at least some of thecontingency resource instance(s), and continuing (or resuming) receivingand processing read and/or write requests (as in 1680). For example, anyleased contingency resource instances may be reclaimed by the serviceprovider (or a control plane function of the database system) for theuse of the database table as part of a failover process, to improveperformance by supporting additional scaling or by replacing resourceinstances executing on lower-performance machines/nodes with resourceinstances executing on higher-performance machines/nodes, or for otherreasons, in some embodiments.

Note that while the contingency resource instance management techniquesdescribed again may be particularly well suited to the database systemsdescribed above (e.g., because the database engine head nodes areessentially “stateless”, as most or all of the database state—at leastthe state of the data maintained in the database—is held in or by thedistributed database-optimized storage system), these techniques may beapplied to the management of resource instances for other types ofstateless virtual computing services, in other embodiments.

One embodiment of a method for designating contingency resourceinstances in response to a client request for deployment of a serviceacross availability zones is illustrated by the flow diagram in FIG. 17.As illustrated at 1710, in this example, the method may include aservice provider receiving a request for virtual computing services(e.g., database services, data storage services, computation services,or other computing services) from a client. The method may also includethe service provider provisioning sufficient resource instance capacityin one or more availability zones to provide the requested services, asin 1720. For example, depending on the type of service requested and/orany parameters of any applicable service level agreements (e.g.,parameters specifying a desired level of durability, consistency,availability, etc.), the service provider may provision enough storageinstance capacity, computation capacity, IOPS capacity, etc. to be ableto provide the requested service. In some embodiments, some of thisprimary resource instance capacity (or various components of the primaryresource instances) may be deployed across availability zones (e.g., dueto issues of scale), but it may not be sufficient to continue to providethe requested service at the desired performance level following anode-specific or AZ-wide failure or in light of scaling or growth of theservice without additional resource instance capacity.

As illustrated in this example, the method may include the clientexplicitly requesting deployment across multiple availability zones, asin 1730. For example, if the client explicitly requests a multiple-AZdeployment for reasons of durability, security, availability, or otherreason(s), shown as the positive exit from 1730, the method may includethe service provider designating sufficient resource instance capacityin one or more availability zones other than the availability zone(s) onwhich the primary resource instance capacity is implemented in order tobe able to provide the requested services in the event of a failure oranother trigger condition warranting the use of additional orreplacement resource instance capacity, as in 1740. Otherwise, shown asthe negative exit from 1730, this designation may not be performed. Ineither case, the method may include the service provider activating therequested virtual computing service for (or on behalf of) the clientusing the primary resource instance capacity, as in 1750.

Note that in other embodiments, the service provider may designatecontingency resource instance capacity in a secondary AZ by default(e.g., in order to meet its own targets for durability, security,consistency, and/or availability, in order to meet various service levelagreement levels, or as a default policy) rather than in response to anexplicit request from client to do so. In various embodiments, clientsmay or may not be able to specify whether contingency resource instancesare designated on their behalf, as this decision (and any resultingcontingency resource instance designations) may be transparent to theclients.

As noted above, the techniques described herein for managing contingencyresource instance capacity may be applied when providing services otherthan the database services described herein, including for other typesof database or data storage services. One embodiment of a method formanaging contingency resource instance capacity for another type ofdatabase or storage service is illustrated by the flow diagram in FIG.18. As illustrated at 1810, in this example, the method may includeprovisioning primary storage instance capacity and primary computeinstance capacity for a database or storage service in one availabilityzone. For example, one or more compute instances may be provisioned fordatabase or storage system interface and control functions within one ormore primary availability zones or regions. As illustrated in thisexample, the method may also include provisioning secondary storageinstance capacity (e.g., for any of various replication schemes) anddesignating enough contingency compute instance capacity for additionalor replacement interface or control functions (if subsequently needed)in a secondary region or availability zone, as in 1820.

As illustrated at 1830 in FIG. 18, the method may include offering atleast some of the contingency resource instance capacity for lease on aspot market, as described herein. The method may also include theservice receiving and handling service requests using the primarycompute instance capacity, and storing data in both primary andsecondary storage instance capacity (e.g., using storage instances inboth the primary and secondary AZs), as in 1840. If the contingencycompute instance(s) in the secondary availability zone are not neededfor the service (shown as the negative exit from 1850), the service maycontinue receiving and handling service requests using the primarycompute instance capacity, and storing data in both primary andsecondary storage instance capacity (shown as the feedback from 1850 to1840).

If the contingency compute instance(s) in the secondary availabilityzone are needed for the service (shown as the positive exit from 1850),the method may include revoking any leases on contingency resourceinstance capacity held by other services or processes, as in 1860. Forexample, such leases may be revoked and the corresponding contingencyresource instances applied to providing the database or storage servicein response to detecting a trigger condition warranting the use of thecontingency resource instances (e.g., a failure of or loss ofcommunication with a computing node or an entire availability zone, adrop in performance due to poor load balancing, increased scaling, orother issues, performance of a maintenance operation involving oraffecting the primary resource instances, or other trigger conditions,in different embodiments). As illustrated in this example, applying thereclaimed contingency resource instances to providing the database orstorage service may include provisioning one or more of the contingencyresource instance(s) to provide interface and/or control functionalityfor the database or storage service in addition to, or as a replacementfor, the primary resource instance that were previously provisioned forthis purpose, as in 1870.

The techniques described herein may also be applied to other types ofservices (e.g., those that are not, primarily, data storage services).For example, a client that is using a large amount of compute andnetworking capacity (e.g., for video transcoding or another applicationthat requires large amounts of compute and networking capacity) mayrequest that resource instance capacity be available for their use inmultiple AZs, but they may not use all of that capacity at the sametime. In this case, a service provider may be willing to guarantee thatthe requested capacity will be available when needed, but while thecapacity is not being used in a particular AZ, at least some of it maybe offered for lease on the spot market. In addition, in someembodiments, the client may be able to request additional spot capacity(e.g., on top of any reserved and contingent instance capacity). Such asmodel may allow the client to selectively trade-off between the amountof work that can be performed in a given time period and the price ofperforming that work, e.g., by allowing them to perform a baselineamount of work using relatively less expensive reserved resourceinstances or activating contingency and/or spot capacity (which may bepriced higher per instance than reserved instance capacity) when (andonly when) speed is a priority.

One embodiment of a method for managing contingency resource instancecapacity by a web-based services provider is illustrated by the flowdiagram in FIG. 19. As illustrated at 1910, in the example, the methodmay include a service provider provisioning primary resource instancecapacity for a web-based service in one region or availability zone. Forexample, the service provider may be one that provides database, datastorage, computation, and/or other services using pools of resourceinstances of various types, and provisioning primary resource instancecapacity may include reserving resource instance capacity for theexclusive use of the web-based service. As illustrated in this example,the method may include the service provider designating contingencyresource instance capacity in a secondary region or availability zone,as in 1920, but not (at least at this point) reserving it for theexclusive use of the web-based service.

As described herein, the method may include the service provideroffering at least some of the contingency resource instances for leaseon a spot market, as in 1930, while the web-based service receives andhandles service requests the using primary resource instance capacity,as in 1940. While the contingency resource instance(s) are not needed inthe secondary region or availability zone (shown as the negative exitfrom 1950), the method may include the web-based service continuing toreceive and handle service requests using the primary resource instancecapacity. If and when the contingency resource instance(s) are needed inthe secondary region or availability zone (e.g., as additional orreplacement resource instance capacity, in response to a node-specificor AZ-wide failure, a performance or scaling issue, or another triggercondition being met), the method may include the service providerrevoking any leases on the contingency resource instances. This isillustrated in FIG. 19 by the positive exit from 1950 and 1960. Themethod may then include the service provider provisioning the reclaimed(and/or any as-yet-unused) contingency resource instance(s) for use inproviding the web-based service, and the service continuing or resumingreceiving and handling service requests using contingency resourceinstance(s) instead of or in addition to any still-active primaryresource instances, as in 1970.

The methods described herein may in various embodiments be implementedby any combination of hardware and software. For example, in oneembodiment, the methods may be implemented by a computer system thatincludes one or more processors executing program instructions stored ona computer-readable storage medium coupled to the processors. Theprogram instructions may be configured to implement the functionalitydescribed herein (e.g., the functionality of various servers and othercomponents that implement the database services/systems and/or storageservices/systems described herein).

FIG. 20 is a block diagram illustrating a computer system configured toimplement at least a portion of a system that provides web-basedservices using reserved, contingency, and/or interruptible resourceinstance capacity, according to various embodiments. For example,computer system 2000 may be one of a plurality of computing nodes of adistributed system comprising pooled resource instances, and may beconfigured to implement a database engine head node of a database tier,or one of a plurality of storage nodes of a separate distributeddatabase-optimized storage system that stores database tables andassociated metadata on behalf of clients of the database tier, invarious embodiments. In other embodiments, computer system 2000 may(e.g., along with other computer systems or nodes thereof) be configuredto provide other types of services using reserved, contingency, and/orinterruptible resource instance capacity in one or more resourceinstance pools. For example, computer system 2000 may be configured toimplement a portion or all of the functionality of a pricing manager, aresource manager, an interface manager, various resource instances,and/or various execution platforms, as described herein. Computer system2000 may be any of various types of devices, including, but not limitedto, a personal computer system, desktop computer, laptop or notebookcomputer, mainframe computer system, handheld computer, workstation,network computer, a consumer device, application server, storage device,telephone, mobile telephone, or in general any type of computing device.

Computer system 2000 includes one or more processors 2010 (any of whichmay include multiple cores, which may be single or multi-threaded)coupled to a system memory 2020 via an input/output (I/O) interface2030. Computer system 2000 further includes a network interface 2040coupled to I/O interface 2030. In various embodiments, computer system2000 may be a uniprocessor system including one processor 2010, or amultiprocessor system including several processors 2010 (e.g., two,four, eight, or another suitable number). Processors 2010 may be anysuitable processors capable of executing instructions. For example, invarious embodiments, processors 2010 may be general-purpose or embeddedprocessors implementing any of a variety of instruction setarchitectures (ISAs), such as the x86, PowerPC, SPARC, or MIPS ISAs, orany other suitable ISA. In multiprocessor systems, each of processors2010 may commonly, but not necessarily, implement the same ISA. Thecomputer system 2000 also includes one or more network communicationdevices (e.g., network interface 2040) for communicating with othersystems and/or components over a communications network (e.g. Internet,LAN, etc.). For example, a client application executing on system 2000may use network interface 2040 to communicate with a server applicationexecuting on a single server or on a cluster of servers that implementone or more of the components of the database systems described herein.In another example, an instance of a server application executing oncomputer system 2000 may use network interface 2040 to communicate withother instances of the server application (or another serverapplication) that may be implemented on other computer systems (e.g.,computer systems 2090) in the same or a different availability zone.

In the illustrated embodiment, computer system 2000 also includes one ormore persistent storage devices 2060 and/or one or more I/O devices2080. In various embodiments, persistent storage devices 2060 maycorrespond to disk drives, tape drives, solid state memory, other massstorage devices, or any other persistent storage device. Computer system2000 (or a distributed application or operating system operatingthereon) may store instructions and/or data in persistent storagedevices 2060, as desired, and may retrieve the stored instruction and/ordata as needed. For example, in some embodiments, computer system 2000may host a storage system server node, and persistent storage 2060 mayinclude the SSDs attached to that server node.

Computer system 2000 includes one or more system memories 2020 that areconfigured to store instructions and data accessible by processor(s)2010. In various embodiments, system memories 2020 may be implementedusing any suitable memory technology, (e.g., one or more of cache,static random access memory (SRAM), DRAM, RDRAM, EDO RAM, DDR 10 RAM,synchronous dynamic RAM (SDRAM), Rambus RAM, EEPROM,non-volatile/Flash-type memory, or any other type of memory). Systemmemory 2020 may contain program instructions 2025 that are executable byprocessor(s) 2010 to implement the methods and techniques describedherein. In various embodiments, program instructions 2025 may be encodedin platform native binary, any interpreted language such as Java™byte-code, or in any other language such as C/C++, Java™, etc., or inany combination thereof. For example, in the illustrated embodiment,program instructions 2025 include program instructions executable toimplement the functionality of a database engine head node of a databasetier, or one of a plurality of storage nodes of a separate distributeddatabase-optimized storage system that stores database tables andassociated metadata on behalf of clients of the database tier, indifferent embodiments. In some embodiments, program instructions 2025may implement multiple separate clients, server nodes, and/or othercomponents of a web-based services platform (e.g., a pricing manager, aresource manager, an interface manager, various resource instances,and/or various execution platforms).

In some embodiments, program instructions 2025 may include instructionsexecutable to implement an operating system (not shown), which may beany of various operating systems, such as UNIX, LINUX, Solaris™, MacOS™,Windows™, etc. Any or all of program instructions 2025 may be providedas a computer program product, or software, that may include anon-transitory computer-readable storage medium having stored thereoninstructions, which may be used to program a computer system (or otherelectronic devices) to perform a process according to variousembodiments. A non-transitory computer-readable storage medium mayinclude any mechanism for storing information in a form (e.g., software,processing application) readable by a machine (e.g., a computer).Generally speaking, a non-transitory computer-accessible medium mayinclude computer-readable storage media or memory media such as magneticor optical media, e.g., disk or DVD/CD-ROM coupled to computer system2000 via I/O interface 2030. A non-transitory computer-readable storagemedium may also include any volatile or non-volatile media such as RAM(e.g. SDRAM, DDR SDRAM, RDRAM, SRAM, etc.), ROM, etc., that may beincluded in some embodiments of computer system 2000 as system memory2020 or another type of memory. In other embodiments, programinstructions may be communicated using optical, acoustical or other formof propagated signal (e.g., carrier waves, infrared signals, digitalsignals, etc.) conveyed via a communication medium such as a networkand/or a wireless link, such as may be implemented via network interface2040.

In some embodiments, system memory 2020 may include data store 2045,which may be configured as described herein. For example, theinformation described herein as being stored by the database tier (e.g.,on a database engine head node), such as a transaction log, an undo log,cached page data, or other information used in performing the functionsof the database tiers described herein may be stored in data store 2045or in another portion of system memory 2020 on one or more nodes, inpersistent storage 2060, and/or on one or more remote storage devices2070, at different times and in various embodiments. Similarly, theinformation described herein as being stored by the storage tier (e.g.,redo log records, coalesced data pages, and/or other information used inperforming the functions of the distributed storage systems describedherein) may be stored in data store 2045 or in another portion of systemmemory 2020 on one or more nodes, in persistent storage 2060, and/or onone or more remote storage devices 2070, at different times and invarious embodiments. In general, system memory 2020 (e.g., data store2045 within system memory 2020), persistent storage 2060, and/or remotestorage 2070 may store data blocks, replicas of data blocks, metadataassociated with data blocks and/or their state, database configurationinformation, and/or any other information usable in implementing themethods and techniques described herein. In embodiments in whichcomputer system 2000 implements a component of a service other than adatabase service, data store 2045 may store any type of data usable bythat service (including, but not limited to, data input to or generatedby the service, metadata input to or produced by the service, executionparameter values, interruptibilty parameter values, service requestparameter values, service level agreement parameter values, mappingsbetween resource instances and the services for which they are reservedor designated as contingency resources, customer or subscriberinformation, or state information for various resource instances).

In one embodiment, I/O interface 2030 may be configured to coordinateI/O traffic between processor 2010, system memory 2020 and anyperipheral devices in the system, including through network interface2040 or other peripheral interfaces. In some embodiments, I/O interface2030 may perform any necessary protocol, timing or other datatransformations to convert data signals from one component (e.g., systemmemory 2020) into a format suitable for use by another component (e.g.,processor 2010). In some embodiments, I/O interface 2030 may includesupport for devices attached through various types of peripheral buses,such as a variant of the Peripheral Component Interconnect (PCI) busstandard or the Universal Serial Bus (USB) standard, for example. Insome embodiments, the function of I/O interface 2030 may be split intotwo or more separate components, such as a north bridge and a southbridge, for example. Also, in some embodiments, some or all of thefunctionality of I/O interface 2030, such as an interface to systemmemory 2020, may be incorporated directly into processor 2010.

Network interface 2040 may be configured to allow data to be exchangedbetween computer system 2000 and other devices attached to a network,such as other computer systems 2090 (which may implement one or morestorage system server nodes, database engine head nodes, and/or clientsof the database systems described herein), for example. In addition,network interface 2040 may be configured to allow communication betweencomputer system 2000 and various I/O devices 2050 and/or remote storage2070. Input/output devices 2050 may, in some embodiments, include one ormore display terminals, keyboards, keypads, touchpads, scanning devices,voice or optical recognition devices, or any other devices suitable forentering or retrieving data by one or more computer systems 2000.Multiple input/output devices 2050 may be present in computer system2000 or may be distributed on various nodes of a distributed system thatincludes computer system 2000. In some embodiments, similar input/outputdevices may be separate from computer system 2000 and may interact withone or more nodes of a distributed system that includes computer system2000 through a wired or wireless connection, such as over networkinterface 2040. Network interface 2040 may commonly support one or morewireless networking protocols (e.g., Wi-Fi/IEEE 802.11, or anotherwireless networking standard). However, in various embodiments, networkinterface 2040 may support communication via any suitable wired orwireless general data networks, such as other types of Ethernetnetworks, for example. Additionally, network interface 2040 may supportcommunication via telecommunications/telephony networks such as analogvoice networks or digital fiber communications networks, via storagearea networks such as Fibre Channel SANs, or via any other suitable typeof network and/or protocol. In various embodiments, computer system 2000may include more, fewer, or different components than those illustratedin FIG. 20 (e.g., displays, video cards, audio cards, peripheraldevices, other network interfaces such as an ATM interface, an Ethernetinterface, a Frame Relay interface, etc.)

It is noted that any of the distributed system embodiments describedherein, or any of their components, may be implemented as one or moreweb services. For example, a database engine head node within thedatabase tier of a database system may present database services and/orother types of data storage services that employ the distributed storagesystems described herein to clients as web services. In someembodiments, a web service may be implemented by a software and/orhardware system designed to support interoperable machine-to-machineinteraction over a network. A web service may have an interfacedescribed in a machine-processable format, such as the Web ServicesDescription Language (WSDL). Other systems may interact with the webservice in a manner prescribed by the description of the web service'sinterface. For example, the web service may define various operationsthat other systems may invoke, and may define a particular applicationprogramming interface (API) to which other systems may be expected toconform when requesting the various operations.

In various embodiments, a web service may be requested or invokedthrough the use of a message that includes parameters and/or dataassociated with the web services request. Such a message may beformatted according to a particular markup language such as ExtensibleMarkup Language (XML), and/or may be encapsulated using a protocol suchas Simple Object Access Protocol (SOAP). To perform a web servicesrequest, a web services client may assemble a message including therequest and convey the message to an addressable endpoint (e.g., aUniform Resource Locator (URL)) corresponding to the web service, usingan Internet-based application layer transfer protocol such as HypertextTransfer Protocol (HTTP).

In some embodiments, web services may be implemented usingRepresentational State Transfer (“RESTful”) techniques rather thanmessage-based techniques. For example, a web service implementedaccording to a RESTful technique may be invoked through parametersincluded within an HTTP method such as PUT, GET, or DELETE, rather thanencapsulated within a SOAP message.

The various methods as illustrated in the figures and described hereinrepresent example embodiments of methods. The methods may be implementedmanually, in software, in hardware, or in a combination thereof. Theorder of any method may be changed, and various elements may be added,reordered, combined, omitted, modified, etc.

Although the embodiments above have been described in considerabledetail, numerous variations and modifications may be made as wouldbecome apparent to those skilled in the art once the above disclosure isfully appreciated. It is intended that the following claims beinterpreted to embrace all such modifications and changes and,accordingly, the above description to be regarded in an illustrativerather than a restrictive sense.

The invention claimed is:
 1. A computing system, comprising: a pluralityof computing nodes, each of which comprises at least one processor and amemory; wherein one or more resource instances executing on theplurality of computing nodes implement a storage service, and whereinthe storage service comprises a head node and two or more server nodesof a distributed storage service that stores portions of data on one ormore storage devices; wherein one or more other resource instances in aresource instance pool are designated as contingency resource instancesfor the storage service, but are not reserved for the exclusive use ofthe storage service; wherein, while the head node is operating asexpected: the head node is configured to: receive, from a client of thestorage service, one or more write requests, each directed to arespective data item and specifying a modification to be made to therespective data item; and route information about the specifiedmodifications to particular ones of the server nodes of the distributedstorage service; the server nodes of the distributed storage service areconfigured to: apply the specified modifications; and a resourcemanagement component executing on one of the computing nodes isconfigured to lease one or more of the contingency resource instances toa client, wherein leases for the contingency resource instances arerevocable by the resource management component when they are needed forthe use of the storage service; and wherein, in response to determiningthat the head node is no longer operating as expected, the resourcemanagement component is configured to: revoke a lease for at least oneof the one or more contingency resource instances; reserve the at leastone of the contingency resource instances for the use of the storageservice; and instantiate another head node using the at least one of thecontingency resource instances.
 2. The system of claim 1, wherein the atleast one of the contingency resource instances is hosted on a given oneof the plurality of computing nodes other than a computing node on whichthe head node is implemented.
 3. The system of claim 1, wherein thecontingency resource instances are hosted in a different availabilityzone or region than one or more availability zones or regions in whichthe resource instances are hosted.
 4. The system of claim 3, wherein asubset of the two or more server nodes of the distributed storageservice are implemented using reserved resource instances in thedifferent availability zone or region.
 5. The system of claim 1, whereinsaid determining that the head node is no longer operating as expectedcomprises detecting a failure of a computing node on which the head nodewas implemented.
 6. The system of claim 1, wherein, for each of the oneor more write requests, said routing comprises: generating a redo logrecord representing the modification to be made to the given data item;and sending the redo log record, but not a data page comprising thegiven data item, to a particular server node of the distributed storageservice that stores a version of the data page comprising the given dataitem; and wherein, for each of the one or more write requests, saidapplying the modification comprises: receiving the redo log record fromthe head node; writing the redo log record to one or more storagedevices; returning, to the head node, an acknowledgement that the redolog record was written; and subsequent to returning the acknowledgement:generating a current version of the data page comprising the given datarecord, wherein to generate the current version of the data page, theparticular server node of the distributed storage service is configuredto apply the received redo log record and one or more other redo logrecords representing modifications to the data page to a previouslystored version of the data page; and writing the current version of thedata page to one or more storage devices.
 7. A method, comprising:performing by one or more computers: receiving a request for databaseservices, wherein the request specifies that a database should bedeployed on the one or more computers; reserving primary resourceinstance capacity for the database, wherein the primary resourceinstance capacity is sufficient to implement the requested database;designating contingency resource instance capacity for the database;while the database operates as expected using the primary resourceinstance capacity: receiving and routing database queries to one or morestorage nodes using the primary resource instance capacity; and leasingat least a portion of the contingency resource instance capacity,wherein said leasing comprises providing the at least a portion of thecontingency resource instance capacity for a use by an entity other thanthe database until and unless a trigger condition is detected indicatingthat it is needed by the database; detecting a trigger conditionindicating that the at least a portion of the contingency resourceinstance capacity is needed by the database; and in response to saiddetecting, revoking a lease on the at least a portion of the contingencyresource instance capacity.
 8. The method of claim 7, furthercomprising, in response to said detecting: reserving the at least aportion of the contingency resource instance capacity for the database;and instantiating one or more resource instances of the at least aportion of the contingency resource instance capacity as additionalresource instances for the database or as replacements for one or moreprimary resource instances for the database.
 9. The method of claim 7,wherein said reserving comprises reserving the primary resource instancecapacity for the database in one or more availability zones; whereinsaid designating comprises designating the contingency resource instancecapacity for the database in an availability zone other than the one ormore availability zones; and wherein said detecting a trigger conditioncomprises detecting a failure of a computing node in one of the one ormore availability zones on which one or more instances of the primaryresource instance capacity were executing.
 10. The method of claim 7,wherein said reserving comprises reserving the primary resource instancecapacity for the database in one or more availability zones; whereinsaid designating comprises designating the contingency resource instancecapacity for the database in an availability zone other than the one ormore availability zones; and wherein said detecting a trigger conditioncomprises detecting a failure affecting availability of all computingnodes in one of the one or more availability zones.
 11. The method ofclaim 7, wherein said detecting a trigger condition comprises detectinga failure of a computing node on which one or more resource instances ofthe primary resource instance capacity were executing; wherein themethod further comprises, in response to said detecting, designating theone or more resource instances of the primary resource instance capacityas contingency resource instances for the database.
 12. The method ofclaim 7, wherein said designating comprises designating one or moreparticular resource instances as contingency resource instances for thedatabase.
 13. The method of claim 7, wherein pricing for designatingeach of the resource instances of the contingency resource instancecapacity is lower than pricing for reserving each of the resourceinstances of the primary resource instance capacity.
 14. The method ofclaim 7, wherein pricing for leasing each of the resource instances ofthe contingency resource instance capacity is lower than pricing forreserving each of the resource instances of the primary resourceinstance capacity.
 15. A non-transitory, computer-readable storagemedium storing program instructions that when executed on one or morecomputers cause the one or more computers to collectively implement oneor more services, wherein the program instructions cause the one or morecomputers to perform: provisioning a plurality of resource instances asa pool of resource instances for one of the one or more services;designating one or more other resource instances as a pool ofcontingency resource instances for the one of the one or more services;providing the one of the one or more services using resource instancesin the pool of resource instances; leasing at least a portion of theresource instances in the pool of contingency resource instances for useby another one of the one or more services; detecting a conditionwarranting use of the at least a portion of the resource instances inthe pool of contingency resource instances by the one of the one or moreservices; in response to said detecting: revoking a lease on the atleast a portion of the resource instances in the pool of contingencyresource instances; removing the at least a portion of the resourceinstances in the pool of contingency resource instances from the pool ofcontingency resource instances; and provisioning the at least a portionof the resource instances removed from the pool of contingency resourceinstances as resource instances for the one of the one or more services.16. The non-transitory, computer-readable storage medium of claim 15,wherein said detecting a condition comprises detecting a failurecondition on the one or more computers.
 17. The non-transitory,computer-readable storage medium of claim 15, wherein said detecting acondition comprises detecting that a scaling of the one of the one ormore services cannot be supported using the pool of resource instances.18. The non-transitory, computer-readable storage medium of claim 15,wherein said detecting a condition comprises determining thatperformance of the one of the one or more services would be improved byprovisioning the at least a portion of the resource instances removedfrom the pool of contingency resource instances as additional resourceinstances for the one of the one or more services or as replacements forone or more of the resource instances for the one of the one or moreservices.
 19. The non-transitory, computer-readable storage medium ofclaim 15, wherein the one of the one or more services comprises adatabase service or a data storage service.